13.6 Knowledge-Based Vision

Chapter Contents (Back)
Recognition, Model Based. Model Based Recognition. Object Recognition. Matching, Models. Knowledge. High Level Vision.

13.6.1 General Issues -- Knowledge-Based Vision

Chapter Contents (Back)
Matching, Models. Knowledge. Knowledge-Based Vision.
See also Context, Fine-Grained Classification.

Uhr, L.[Leonard], and Vossler, C.[Charles],
A Pattern-Recognition Program that Generates, Evaluates, and Adjusts Its Own Operators,
CandT(251-268), 1963. BibRef 6300
Earlier: WJCC(19), 1961, pp. 555-570. Recognition using a series of operators (patterns, binary masks). BibRef

Sauvain, R.W., Uhr, L.,
A teachable pattern describing and recognizing program,
PR(1), No. 3, March 1969, pp. 219-232.
Elsevier DOI 0309
Learns coded line drawings. BibRef

Uhr, L.,
Layered Recognition Cone Networks That Preprocess Classify and Describe,
TC(21), No. 7, July 1972, pp. 758-768. Pyramids. Multiple Resolutions. Early precursor to the UMass work. BibRef 7207

Uhr, L.[Leonard], and Douglass, R.[Robert],
A Parallel-Serial Recognition Cone System for Perception: Some Test Results,
PR(11), No. 1, 1979, pp. 29-39.
Elsevier DOI BibRef 7900
Earlier:
'Recognition Cones,' and Some Test Results; The Imminent Arrival of Well-Structured Parallel-Serial computers; Positions, and Positions on Positions,
CVS78(363-377). BibRef
Earlier:
A 'Recognition Cone' Perceptual System: Brief Test Results,
IJCAI77(597). BibRef

Uhr, L.,
'Recognition Cones' That Perceive and Describe Scenes that Move and Change Over Time,
ICPR76(287-293). BibRef 7600

Uhr, L.[Leonard],
Flexible linguistic pattern recognition,
PR(3), No. 4, November 1971, pp. 363-383.
Elsevier DOI 0309
BibRef

Hayes-Roth, F.[Frederick],
Schematic classification problems and their solution,
PR(6), No. 2, October 1974, pp. 105-113.
Elsevier DOI 0309
BibRef

Hayes-Roth, F.[Frederick],
Representation of structured events and efficient procedures for their recognition,
PR(8), No. 3, July 1976, pp. 141-150.
Elsevier DOI 0309
Structured events. BibRef

Briot, M., Renaud, M., Stojiljkovic, Z.,
An Approach to Spatial Pattern Recognition of Solid Objects,
SMC(8), 1978, pp. 690-694. BibRef 7800

Kovalevsky, V.A.,
Local versus Global Decisions in Image Recognition,
PIEEE(67), 1979, pp. 745-752. BibRef 7900

Tenenbaum, J.M.[Jay M.], Fischler, M.A.[Martin A.], Barrow, H.G.[Harry G.],
Scene Modeling: A Structural Basis for Image Description,
CGIP(12), No. 4, April 1980, pp. 407-425.
Elsevier DOI BibRef 8004

Barrow, H.G., and Tenenbaum, J.M.,
MSYS: A System for Reasoning about Scenes,
SRI AICenterTN 108, 1975. BibRef 7500
And: SRI AIMemo121, April 1976. Knowledge-Based Vision. System: MSYS. The MSYS Report. Use inexact reasoning on uncertain data to interpret regions extracted from an image. MSYS is an asynchronous relaxation process that applies the rules imposed by the modeluntil the labels are consistent. Constraints such as surface height and orientation can bu used. Relations between objects in the scene (hence regions in the image) can be used.. An M* (modified A*) search is used. For application in IGS:
See also Experiments in Interpretation Guided Segmentation. BibRef

Kunii, T.L., Weyl, S., Tenenbaum, J.M.,
A Relational Data Base Schema for Describing Complex Pictures with Color and Texture,
ICPR74(310-316). BibRef 7400

Tenenbaum, J.M., Weyl, S.,
A Region-Analysis System for Interactive Scene Analysis,
IJCAI75(682-687). BibRef 7500

Tenenbaum, J.M.,
On Locating Objects by Their Distinguishing Features in Multisensory Images,
CGIP(2), No. 3, December 1973, pp. 308-320. BibRef 7312
And: SRI-TN-84, 1973. Early version of old SRI work. A good reference for basic techniques for description based extraction. BibRef

Tenenbaum, J.M.,
Object Recognition in Multi-Sensory Scene Analysis,
SRI AIMemo84, September 1973. Acquisition and validation. Turned into MSYS and related work. BibRef 7309

Nitzan, D.,
Object Recognition in Multisensory Scene Analysis,
SRI AIMemo83, November 1973. BibRef 7311

Garvey, T.D.,
Perceptual Strategies for Purposive Vision,
SRITechnical Note 117, September 1976. BibRef 7609

Garvey, T.D., and Tenenbaum, J.M.,
On the Automatic Generation of Programs for Locating Objects in Office Scenes,
ICPR74(162-168). Another of the early papers. BibRef 7400

toe Water, F.T.B.[Frits T. Beukema], Duin, R.P.W.[Robert P. W.],
Dealing with a priori knowledge by fuzzy labels,
PR(14), No. 1-6, 1981, pp. 111-115.
Elsevier DOI 0309
BibRef

Tsotsos, J.K.[John K.],
Knowledge and the Visual Process: Content, Form and Use,
PR(17), No. 1, 1984, pp. 13-27.
Elsevier DOI BibRef 8400
And: (Knowledge of...) ICPR82(654-669). BibRef

van Cleynenbruegel, J., Fierens, F., Suetens, P., Oosterlinck, A.,
Knowledge-Based Improvement of Automatic Image Interpretation for Restricted Scenes: Two Case Studies,
IVC(6), No. 4, November 1988, pp. 238-246.
Elsevier DOI BibRef 8811

Chen, S.,
An Intelligent Computer Vision System,
IJIS(1), 1986, pp. 15-28. BibRef 8600

Andress, K.M., and Kak, A.C.,
Evidence Accumulation and Flow of Control in a Hierarchial Spatial Reasoning System,
AIMag(9), No. 2, Summer 1988, pp. 75-94. BibRef 8800
And: ASR-I90(Ch. 4). BibRef
And:
A Production System Environment for Integrating Knowledge with Vision Data,
SRMSF87(1-12). Blackboard. BibRef

Woods, P.W.[Peter W.], Pycock, D.[David], Taylor, C.J.[Christopher J.],
A Frame-Based System for Modelling and Executing Visual Tasks,
IVC(7), No. 2, May 1989, pp. 102-108.
Elsevier DOI BibRef 8905

Trivedi, M.M., Abidi, M.A., Eason, R.O., and Gonzalez, R.C.,
Developing Robotic Systems with Multiple Sensors,
SMC(20), No. 6, November/December, 1990, pp. 1285-1300. BibRef 9011
Earlier:
Object Recognition and Pose Determination in Multi Sensor Robotic Systems,
SMC-C89(xx-yy). Pose Estimation. BibRef

Hopkins, S., Michaelson, G.J., Wallace, A.M.,
Parallel Imperative and Functional Approaches to Visual Scene Labelling,
IVC(7), No. 3, August 1989, pp. 178-193.
Elsevier DOI BibRef 8908

Rosin, P.L.[Paul L.], Ellis, T.[Tim],
Frame-Based System for Image Interpretation,
IVC(9), No. 6, December 1991, pp. 353-361.
Elsevier DOI Interpretation in Prolog. Trigger C coded image processing. BibRef 9112

Ellis, T.J., Rosin, P.L., and Golton, P.,
Model-Based Vision for Automatic Alarm Detection,
AeroSysMag(6), 1990, pp. 14-20. BibRef 9000

Lee, C.M., Pong, T.C., Slagle, J.R.,
A Knowledge-Based System for the Image Correspondence Problem,
PRAI(4), 1990, pp. 45-55. BibRef 9000

Meisels, A.,
Levels of Knowledge for Object Extraction,
MVA(4), 1991, pp. 183-192. BibRef 9100

Kakusho, K., Dan, S., Kitahashi, T., and Abe, N.,
Computer Vision Based on a Hypothesization and Verification Scheme by Parallel Relaxation,
IJCV(9), No. 1, October 1992, pp. 13-30.
Springer DOI Relaxation. Shape from Single Image. Recovery of shape from a monocular image. BibRef 9210

Kakusho, K., Dan, S., Abe, N., and Kitahashi, T.,
Shape Recovery and Error Correction Based on Hypothetical Constraints by Parallel Network for Energy Minimization,
PRAI(8), 1994, pp. 577-593. BibRef 9400

Lederman, S.J., Klatzky, R.L.,
The Intelligent Hand: An Experimental Approach to Human Object Recognition and Implications for Robotics and AI,
AIMag(15), No. 1, Spring 1994, pp. 26-38. BibRef 9400

Eklundh, J.O.,
Knowledge Based Image Analysis,
TRITA-NA-8206 (Integral 2), March 1982. BibRef 8203

Wallace, A.M.[Andrew M.],
A Comparison of Approaches to High-Level Image Interpretation,
PR(21), No. 3, 1988, pp. 241-259.
Elsevier DOI BibRef 8800

Grenander, U.[Ulf], Miller, M.I.,
Representation of Knowledge in Complex Systems,
RoyalStat(B-56), No. 4, 1994, pp. 569-603. 9702
BibRef

Aviad, Z., Lozinskii, E.,
On a Conceptual Description of Images,
PRL(3), 1985, pp. 51-57. BibRef 8500

Pham, D.T., Dimov, S.S.,
An Efficient Algorithm for Automatic Knowledge Acquisition,
PR(30), No. 7, July 1997, pp. 1137-1143.
Elsevier DOI 9707
BibRef

Edelman, S., Duvdevani-Bar, S.,
Similarity, Connectionism, and the Problem of Representation in Vision,
NeurComp(9), No. 4, May 15 1997, pp. 701-720. 9706
BibRef

Duvdevani-Bar, S.[Sharon], Edelman, S.[Shimon],
Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes,
IJCV(33), No. 3, September 1999, pp. 201-228.
DOI Link BibRef 9909

Mirmehdi, M., Palmer, P.L., Kittler, J.V., Dabis, H.S.,
Feedback Control Strategies for Object Recognition,
IP(8), No. 8, August 1999, pp. 1084-1101.
IEEE DOI BibRef 9908
Earlier:
Multi-pass Feedback Control for Object Recognition,
VI96(49-56).
PS File. BibRef
Earlier:
Complex Feedback Strategies for Hypothesis Generation and Verification,
BMVC96(Poster Session 1). 9608
Optimization technique with feedback. University of Surrey BibRef

Lesser, V.R.[Victor R.], Nawab, H.[Hamid], Klassner, F.I.[Frank I.],
IPUS: An Architecture for the Integrated Processing and Understanding of Signals,
AI(77), No. 1, October 1995, pp. 129-171.
Elsevier DOI BibRef 9510

Kelly, M.F.[Michael F.], and Levine, M.D.[Martin D.],
Finding and Describing Objects in Complex Images,
AIU96(209-226). Descriptions, Parts. Various filter/operators on the images. BibRef 9600

Bourbakis, N.G., Mertoguno, J.S.,
Kydon: An Autonomous, Multilayer Image-Understanding System - Lower Layers,
EngAAI(9), No. 1, February 1996, pp. 43-52. BibRef 9602

Roli, F., Serpico, S.B., Vernazza, G.,
A Hybrid System For 2-Dimensional Image Recognition,
PIEEE(84), No. 11, November 1996, pp. 1659-1681. 9611
BibRef

Dellepiane, S.G., Venturi, G., Vernazza, G.L.,
Model Generation and Model Matching of Real Images by a Fuzzy Approach,
PR(25), No. 2, February 1992, pp. 115-137.
Elsevier DOI BibRef 9202

Dellepiane, S.G., Serpico, S.B., Vernazza, G.L.,
Analysis and Classification of SAR Images by a Knowledge-Based Approach,
ICPR88(II: 1207-1209).
IEEE DOI BibRef 8800

Kuruppu, N.R.,
The Development of a BAM System Using a Delta-Rule Based Algorithm (The DBAM System),
PRL(17), No. 11, September 16 1996, pp. 1151-1155. 9611
BibRef

Gamage, L.B., Gosine, R.G., de Silva, C.W.,
Extraction of Rules from Natural Objects for Automated Mechanical Processing,
SMC-A(26), No. 1, January 1996, pp. 105-120.
IEEE Top Reference. BibRef 9601

Chan, S.W.K., Leung, K.S., Wong, W.S.F.,
Object-Oriented Knowledge-Based System for Image Diagnosis,
AppAI(10), No. 5, September/October 1996, pp. 407-438. 9611
BibRef

Kontoes, C.C., Rokos, D.,
The Integration of Spatial Context Information in an Experimental Knowledge-Based System and the Supervised Relaxation Algorithm: 2 Successful Approaches to Improving Spot-Xs Classification,
JRS(17), No. 16, November 10 1996, pp. 3093-3106. 9611
BibRef

Moody, J.[John], Flynn, P.J.[Patrick J.], Cohn, D.L.[David L.],
Parallel Hypothesis Verification,
PR(26), No. 10, October 1993, pp. 1521-1527.
Elsevier DOI BibRef 9310
Earlier: ICPR92(IV:107-110).
IEEE DOI 9208
BibRef

Tönjes, R., Growe, S., Bückner, J., Liedtke, C.E.,
Knowledge-Based Interpretation of Remote Sensing Images Using Semantic Nets,
PhEngRS(65), No. 7, July 1999, pp. 811. Uses knowledge about landscape scenes and map information from GIS. BibRef 9907

Draper, B.A.[Bruce A.], Bins, J.[Jose], Baek, K.[Kyungim],
ADORE: Adaptive Object Recognition,
Videre(1), No. 4, Winter 2000, pp. xx-yy. 0005
BibRef
Earlier: CVS99(522 ff.).
Springer DOI 0209
BibRef

Draper, B.A.[Bruce A.], Baek, K.[Kyungim], Boody, J.[Jeff],
Implementing the Expert Object Recognition Pathway,
MVA(16), No. 1, December 2004, pp. 27-32.
Springer DOI 0501
BibRef
Earlier: CVS03(1 ff).
Springer DOI 0306
BibRef

Drummond, T.W.[Tom W.], Caelli, T.M.[Terry M.],
Learning Task-Specific Object Recognition and Scene Understanding,
CVIU(80), No. 3, December 2000, pp. 315-348.
DOI Link 0012
BibRef

Caelli, T.M., and Bischof, W.F.,
Machine Learning Paradigms for Pattern Recognition and Image Understanding,
SV(10), 1996, pp. 87-103. BibRef 9600

Caelli, T.M.[Terry M.], and Bischof, W.F.[Walter F.],
Machine Learning and Image Interpretation,
PlenumPress, 1997. ISBN: 0-306-45761-X. 448 pp. Authors from School of Computing, Curtin University of Technology, Perth, Australia. BibRef 9700

Blake, R.E.[Richard E.], Juozapavicius, A.[Algimantas],
Convergent matching for model-based computer vision,
PR(36), No. 2, February 2003, pp. 527-534.
Elsevier DOI 0211
BibRef

Ogiela, M.R.[Marek R.], Tadeusiewicz, R.[Ryszard],
Artificial intelligence structural imaging techniques in visual pattern analysis and medical data understanding,
PR(36No. 10, October 2003, pp. 2441-2452.
Elsevier DOI 0308

See also Graph image language techniques supporting radiological, hand image interpretations. BibRef

Rosin, P.L.[Paul L.], Rana, O.F.[Omer F.],
Special Issue Introduction: Agent-based computer vision,
PR(37), No. 4, April 2004, pp. 627-629.
Elsevier DOI 0403
BibRef

Ogale, A.S.[Abhijit S.], Aloimonos, Y.[Yiannis],
A Roadmap to the Integration of Early Visual Modules,
IJCV(72), No. 1, April 2007, pp. 9-25.
Springer DOI 0001
BibRef

Neumann, B.[Bernd], Möller, R.[Ralf],
On scene interpretation with description logics,
IVC(26), No. 1, 1 January 2008, pp. 82-101.
Elsevier DOI 0711
BibRef
Earlier: CogVis03(247-275).
Springer DOI 0310
Scene interpretation; Description logics; High-level vision BibRef

Schroeder, C.[Carsten], Neumann, B.[Bernd],
On the Logics of Image Interpretation: Model Construction in a Formal Knowledge-Representation Framework,
ICIP96(II: 785-788).
IEEE DOI BibRef 9600

Hogg, D.C.[David C.], Neumann, B.[Berndt],
Knowledge Intensive Image Interpretation: Introduction,
ICIP96(18A2). BibRef 9600

Ponce, J.[Jean], Hebert, M.[Martial], Schmid, C.[Cordelia], and Zisserman, A.[Andrew], (Eds.)
Toward Category-Level Object Recognition,
CLOR06LCNS Volume 4170, 2006.
Springer DOI The papers selected and assembled from 2 workshops in 2003 and 2004. BibRef 0600

Treiber, M.A.[Marco Alexander],
An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications,
Springer2010, ISBN: 978-1-84996-234-6
WWW Link. Algorithm descriptions. Buy this book: An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications (Advances in Pattern Recognition) 1010
BibRef

Kleiner, I.[Igor], Keren, D.[Daniel], Newman, I.[Ilan], Ben-Zwi, O.[Oren],
Applying Property Testing to an Image Partitioning Problem,
PAMI(33), No. 2, February 2011, pp. 256-265.
IEEE DOI 1101
Quick test to determine whether to continue analysis. BibRef

Hata, S.[Seiji],
Tailor-made engineering in image processing industry,
FCV11(1-2).
IEEE DOI 1102
To date computer vision applications are custom made. Discuss attempts to improve this. BibRef

Falomir, Z.[Zoe], Museros, L.[Lledó], Gonzalez-Abril, L.[Luis], Escrig, M.T.[M. Teresa], Ortega, J.A.[Juan A.],
A model for the qualitative description of images based on visual and spatial features,
CVIU(116), No. 6, June 2012, pp. 698-714.
Elsevier DOI 1204
Qualitative shape; Qualitative colours; Qualitative orientation; Spatial description Main visual features (shape and color) and the main spatial features (fixed orientation, relative orientation and topology) of each object within the image. BibRef

Sanz, I.[Ismael], Museros, L.[Lledó], Falomir, Z.[Zoe], Gonzalez-Abril, L.[Luis],
Customising a qualitative colour description for adaptability and usability,
PRL(67, Part 1), No. 1, 2015, pp. 2-10.
Elsevier DOI 1511
Colour naming
See also Measures of similarity between qualitative descriptions of shape, colour and size applied to mosaic assembling. BibRef

Falomir, Z.[Zoe], Museros, L.[Lledó], Castelló, V.[Vicent], Gonzalez-Abril, L.[Luis],
Qualitative distances and qualitative image descriptions for representing indoor scenes in robotics,
PRL(34), No. 7, 1 May 2013, pp. 731-743.
Elsevier DOI 1303
Sensor data integration; Fuzzy logic; Qualitative shape; Qualitative colour; Topology; Qualitative spatial orientation BibRef

Li, C.C.[Cong-Cong], Kowdle, A.[Adarsh], Saxena, A.[Ashutosh], Chen, T.H.[Tsu-Han],
Toward Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models,
PAMI(34), No. 7, July 2012, pp. 1394-1408.
IEEE DOI 1205
Scene understanding, classification, machine learning, robotics. Jointly optimize depth, categorization, object detection. BibRef

Moghaddam, R.F., Cheriet, M.,
Real-Time Knowledge-Based Processing of Images: Application of the Online NLPM Method to Perceptual Visual Analysis,
IP(21), No. 8, August 2012, pp. 3390-3404.
IEEE DOI 1208
BibRef

Yu, L., Xie, J., Chen, S.,
Conditional random field-based image labelling combining features of pixels, segments and regions,
IET-CV(6), No. 5, 2012, pp. 459-467.
DOI Link 1210
Single layer segment based CRF method. BibRef

Maji, S.[Subhransu], Berg, A.C.[Alexander C.], Malik, J.[Jitendra],
Efficient Classification for Additive Kernel SVMs,
PAMI(35), No. 1, January 2013, pp. 66-77.
IEEE DOI 1212
BibRef

Zhang, H.[Hao], Berg, A.C.[Alexander C.], Maire, M.[Michael], Malik, J.[Jitendra],
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition,
CVPR06(II: 2126-2136).
IEEE DOI 0606
BibRef

Ordonez, V.[Vicente], Liu, W.[Wei], Deng, J.[Jia], Choi, Y.[Yejin], Berg, A.C.[Alexander C.], Berg, T.L.[Tamara L.],
Learning to Name Objects,
CACM(59), No. 3, March 2016, pp. 108-115.
DOI Link 1604
BibRef

Chen, X.W.[Xiao-Wu], Li, Q.[Qing], Zhao, D.Y.[Dong-Yue], Zhao, Q.P.[Qin-Ping],
Occlusion cues for image scene layering,
CVIU(117), No. 1, January 2013, pp. 42-55.
Elsevier DOI 1212
Human perception; Occlusion cues; Occlusion prediction; Layering BibRef

Yue, P.[Peng], Di, L.P.[Li-Ping], Wei, Y.X.[Ya-Xing], Han, W.G.[Wei-Guo],
Intelligent services for discovery of complex geospatial features from remote sensing imagery,
PandRS(83), No. 1, 2013, pp. 151-164.
Elsevier DOI 1308
Image mining for compex features (e.g. collection of buildings, not just a single complex building). BibRef

Pavlidis, T.[Theo],
The challenge of general machine vision,
SIViP(8), No. 1, January 2014, pp. 191-195.
WWW Link. 1402
BibRef

Quinton, J.C., Volpi, N.C., Barca, L., Pezzulo, G.,
The Cat is on the Mat. or is it a Dog? Dynamic Competition in Perceptual Decision Making,
SMCS(44), No. 5, May 2014, pp. 539-551.
IEEE DOI 1405
decision making BibRef

Smith, J.R.[John R.],
How Many Visual Concepts?,
MultMedMag(21), No. 1, January 2014, pp. 2-3.
IEEE DOI 1405
Scene analysis BibRef

Xie, Y.R.[Yu-Rui], Wu, Q.B.[Qing-Bo], Luo, B.[Bing], Huang, C.[Chao], Tang, L.Z.[Liang-Zhi],
A Combing Top-Down and Bottom-Up Discriminative Dictionaries Learning for Non-specific Object Detection,
IEICE(E97-D), No. 5, May 2014, pp. 1367-1370.
WWW Link. 1405
BibRef

Xie, Y.R.[Yu-Rui], Wu, Q.B.[Qing-Bo], Luo, B.[Bing],
Discriminative Semantic Parts Learning for Object Detection,
IEICE(E98-D), No. 7, July 2015, pp. 1434-1438.
WWW Link. 1508
BibRef

Sun, M.[Min], Kim, B.S.[Byung-Soo], Kohli, P.[Pushmeet], Savarese, S.[Silvio],
Relating Things and Stuff via ObjectProperty Interactions,
PAMI(36), No. 7, July 2014, pp. 1370-1383.
IEEE DOI 1407
BibRef
Earlier: A2, A1, A3, A4:
Relating Things and Stuff by High-Order Potential Modeling,
Global12(III: 293-304).
Springer DOI 1210
Detectors. the object and background. BibRef

Wang, S.[Shuo], Wang, Y.Z.[Yi-Zhou],
Weakly Supervised Semantic Segmentation with a Multiscale Model,
SPLetters(22), No. 3, March 2015, pp. 308-312.
IEEE DOI 1410
Buildings BibRef

Wang, S.[Shuo], Wang, Y.Z.[Yi-Zhou], Zhu, S.C.[Song-Chun],
Learning Hierarchical Space Tiling for Scene Modeling, Parsing and Attribute Tagging,
PAMI(37), No. 12, December 2015, pp. 2478-2491.
IEEE DOI 1512
BibRef
Earlier:
Hierarchical Space Tiling for Scene Modeling,
ACCV12(II:796-810).
Springer DOI 1304
attribute grammars BibRef

Wang, S.[Shuo], Joo, J.[Jungseock], Wang, Y.Z.[Yi-Zhou], Zhu, S.C.[Song-Chun],
Weakly Supervised Learning for Attribute Localization in Outdoor Scenes,
CVPR13(3111-3118)
IEEE DOI 1309
Hierarchical Space Tiling (HST). Learn parts and attributs given captions. BibRef

Aloimonos, Y.[Yiannis], Fermüller, C.[Cornelia],
The Cognitive Dialogue: A new model for vision implementing common sense reasoning,
IVC(34), No. 1, 2015, pp. 42-44.
Elsevier DOI 1502
Vision and language. Vision is part of an intelligent system that reasons, not just vision by itself. BibRef

Aditya, S.[Somak], Yang, Y.Z.[Ye-Zhou], Baral, C.[Chitta], Aloimonos, Y.[Yiannis], Fermüller, C.[Cornelia],
Image Understanding using vision and reasoning through Scene Description Graph,
CVIU(173), 2018, pp. 33-45.
Elsevier DOI 1901
Image Understanding, Commonsense Reasoning, Vision, Reasoning BibRef

Guo, R.Q.[Rui-Qi], Hoiem, D.[Derek],
Labeling Complete Surfaces in Scene Understanding,
IJCV(112), No. 2, April 2015, pp. 172-187.
WWW Link. 1504
BibRef
Earlier:
Beyond the Line of Sight: Labeling the Underlying Surfaces,
ECCV12(V: 761-774).
Springer DOI 1210
infer hidden regions BibRef

Lindner, A.[Albrecht], Susstrunk, S.,
Semantic-Improved Color Imaging Applications: It Is All About Context,
MultMed(17), No. 5, May 2015, pp. 700-710.
IEEE DOI 1505
Computer vision BibRef

Lindner, A.[Albrecht],
Semantic Awareness for Automatic Image Interpretation,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
DOI Link 1407
Ph.D.. Thesis. BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Feng, J.S.[Jian-Shi], Jia, K., Huang, Z.Y.[Zhong-Yang], Yan, S.C.[Shui-Cheng],
Looking Inside Category: Subcategory-Aware Object Recognition,
CirSysVideo(25), No. 8, August 2015, pp. 1322-1334.
IEEE DOI 1508
Data mining BibRef

Dong, J.[Jian], Xia, W.[Wei], Chen, Q.A.[Qi-Ang], Feng, J.S.[Jian-Shi], Huang, Z.Y.[Zhong-Yang], Yan, S.C.[Shui-Cheng],
Subcategory-Aware Object Classification,
CVPR13(827-834)
IEEE DOI 1309
Ambiguity Modeling; Classification; Subcategory Mining BibRef

Liu, X.H.[Xiong-Hao], Yang, W.[Wei], Lin, L.[Liang], Wang, Q.[Qing], Cai, Z.Q.[Zhao-Quan], Lai, J.H.[Jian-Huang],
Data-Driven Scene Understanding with Adaptively Retrieved Exemplars,
MultMedMag(22), No. 3, July 2015, pp. 82-92.
IEEE DOI 1508
Computer graphics. Recover examples from database, then propogate pixel labels. BibRef

Zitnick, C.L.[C. Lawrence], Vedantam, R.[Ramakrishna], Parikh, D.[Devi],
Adopting Abstract Images for Semantic Scene Understanding,
PAMI(38), No. 4, April 2016, pp. 627-638.
IEEE DOI 1603
Abstracts BibRef

Vedantam, R.[Ramakrishna], Lin, X.[Xiao], Batra, T.[Tanmay], Zitnick, C.L.[C. Lawrence], Parikh, D.[Devi],
Learning Common Sense through Visual Abstraction,
ICCV15(2542-2550)
IEEE DOI 1602
Cognition. More than just text. BibRef

Fang, Q., Xu, C.S.[Chang-Sheng], Sang, J., Hossain, M.S.[M. Shamim], Ghoneim, A.[Ahmed],
Folksonomy-Based Visual Ontology Construction and Its Applications,
MultMed(18), No. 4, April 2016, pp. 702-713.
IEEE DOI 1604
Computational modeling BibRef

Yang, X.S.[Xiao-Shan], Zhang, T.Z.[Tian-Zhu], Xu, C.S.[Chang-Sheng], Yan, S.C.[Shui-Cheng], Hossain, M.S.[M. Shamim], Ghoneim, A.[Ahmed],
Deep Relative Attributes,
MultMed(18), No. 9, September 2016, pp. 1832-1842.
IEEE DOI 1609
image recognition BibRef

Malik, J.[Jitendra], Arbeláez, P.[Pablo], Carreira, J.[João], Fragkiadaki, K.[Katerina], Girshick, R.[Ross], Gkioxari, G.[Georgia], Gupta, S.[Saurabh], Hariharan, B.[Bharath], Kar, A.[Abhishek], Tulsiani, S.[Shubham],
The three R's of computer vision: Recognition, reconstruction and reorganization,
PRL(72), No. 1, 2016, pp. 4-14.
Elsevier DOI 1604
Object recognition BibRef

Gori, M.[Marco], Lippi, M.[Marco], Maggini, M.[Marco], Melacci, S.[Stefano],
Semantic video labeling by developmental visual agents,
CVIU(146), No. 1, 2016, pp. 9-26.
Elsevier DOI 1604
Learning from constraints Developmental Visual Agents are life-long learning systems for video understanding. Go from unsupervised feature extraction to symbolic representations. BibRef

Thomas, S.S.[Sinnu Susan], Gupta, S.[Sumana], Subramanian, V.K.[Venkatesh K.],
Perceptual synoptic view-based video retrieval using metadata,
SIViP(11), No. 3, March 2017, pp. 549-555.
WWW Link. 1702
BibRef
Earlier:
Perceptual synoptic view of pixel, object and semantic based attributes of video,
JVCIR(38), No. 1, 2016, pp. 367-377.
Elsevier DOI 1605
Surveillance. Synopsis. Different levels of representation. BibRef

Donatti, G.S.[Guillermo Sebastián],
Memory Organization for Invariant Object Recognition and Categorization,
ELCVIA(15), No. 2, 2016, pp. 33-36.
DOI Link 1611
BibRef

Fan, M.[Miao], Zhou, Q.A.[Qi-Ang], Zheng, T.F.[Thomas Fang], Grishman, R.[Ralph],
Distributed representation learning for knowledge graphs with entity descriptions,
PRL(93), No. 1, 2017, pp. 31-37.
Elsevier DOI 1706
Knowledge, graph BibRef

Lüddecke, T.[Timo], Agostini, A.[Alejandro], Fauth, M.[Michael], Tamosiunaite, M.[Minija], Wörgötter, F.[Florentin],
Distributional semantics of objects in visual scenes in comparison to text,
AI(274), 2019, pp. 44-65.
Elsevier DOI 1908
Object semantics, Vision and language, Semantics, Distributional hypothesis BibRef

Luo, J.[Jie], Wang, Y.F.[Yi-Fei], Jiang, D.C.[Dong-Chen],
Rule-based hidden relation recognition for large scale knowledge graphs,
PRL(125), 2019, pp. 13-20.
Elsevier DOI 1909
Hidden relation, Knowledge graph, Reasoning, OWL2 RL BibRef

Esteban, P.G., Insua, D.R.,
A Model for an Affective Non-Expensive Utility-Based Decision Agent,
AffCom(10), No. 4, October 2019, pp. 498-509.
IEEE DOI 1912
Mood, Computational modeling, Robots, Decision making, Biological system modeling, Decision support systems, utility theory BibRef

Liu, D.[Ding], Wen, B.H.[Bi-Han], Jiao, J.B.[Jian-Bo], Liu, X.M.[Xian-Ming], Wang, Z.Y.[Zhang-Yang], Huang, T.S.[Thomas S.],
Connecting Image Denoising and High-Level Vision Tasks via Deep Learning,
IP(29), 2020, pp. 3695-3706.
IEEE DOI 2002
How denoising can help high level, how high level can help denoising. Deep learning, neural network, image denoising, high-level vision BibRef

van Nuenen, T., Ferrer, X., Such, J.M., Cote, M.,
Transparency for Whom? Assessing Discriminatory Artificial Intelligence,
Computer(53), No. 11, November 2020, pp. 36-44.
IEEE DOI 2010
BibRef

Molinara, M., Bria, A., de Vito, S., Marrocco, C.,
Artificial intelligence for distributed smart systems,
PRL(142), 2021, pp. 48-50.
Elsevier DOI 2101
BibRef

Liu, D.[Daqi], Bober, M.[Miroslaw], Kittler, J.V.[Josef V.],
Visual Semantic Information Pursuit: A Survey,
PAMI(43), No. 4, April 2021, pp. 1404-1422.
IEEE DOI 2103
Visualization, Semantics, Task analysis, Visual perception, Cognition, Object detection, Deep learning, message passing BibRef

Gangopadhyay, B.[Briti], Hazra, S.[Somnath], Dasgupta, P.[Pallab],
Semi-lexical languages: a formal basis for using domain knowledge to resolve ambiguities in deep-learning based computer vision,
PRL(152), 2021, pp. 143-149.
Elsevier DOI 2112
Neuro-symbolic deduction, Semantic interpretation, Explainable inference BibRef

Zhang, M.Y.[Meng-Yang], Tian, G.H.[Guo-Hui], Zhang, Y.[Ying], Duan, P.[Peng],
Reinforcement Learning for Logic Recipe Generation: Bridging Gaps From Images to Plans,
MultMed(24), 2022, pp. 352-365.
IEEE DOI 2202
Reinforcement learning, Feature extraction, Decoding, Artificial neural networks, Generators, Visualization, recipe generation BibRef

Zhao, Y.H.[Yue-Hua], Zhang, J.G.[Ji-Guang], Ma, J.[Jie], Xu, S.B.[Shi-Biao],
Large-Scale Semantic Scene Understanding with Cross-Correction Representation,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Golan, A.[Amos], Foley, D.K.[Duncan K.],
Understanding the Constraints in Maximum Entropy Methods for Modeling and Inference,
PAMI(45), No. 3, March 2023, pp. 3994-3998.
IEEE DOI 2302
Entropy, Bayes methods, Diseases, Systematics, Economics, Data models, Analytical models, Causal inference, constraints, information, principle of maximum entropy BibRef

Duan, X.G.[Xu-Guang], Wang, X.[Xin], Zhao, P.L.[Pei-Lin], Shen, G.Y.[Guang-Yao], Zhu, W.W.[Wen-Wu],
DeepLogic: Joint Learning of Neural Perception and Logical Reasoning,
PAMI(45), No. 4, April 2023, pp. 4321-4334.
IEEE DOI 2303
Combine neural and logical frameworks. Cognition, Optimization, Task analysis, Semantics, Deep learning, Convergence, Artificial neural networks, perceptual reasoning BibRef

Gao, C.[Chen], Liu, S.[Si], Chen, J.[Jinyu], Wang, L.T.[Lu-Ting], Wu, Q.[Qi], Li, B.[Bo], Tian, Q.[Qi],
Room-Object Entity Prompting and Reasoning for Embodied Referring Expression,
PAMI(46), No. 2, February 2024, pp. 994-1010.
IEEE DOI 2401
BibRef

Gao, C.[Chen], Chen, J.[Jinyu], Liu, S.[Si], Wang, L.T.[Lu-Ting], Zhang, Q.[Qiong], Wu, Q.[Qi],
Room-and-Object Aware Knowledge Reasoning for Remote Embodied Referring Expression,
CVPR21(3063-3072)
IEEE DOI 2111
Visualization, Correlation, Navigation, Linguistics, Transformers, Cognition, Pattern recognition BibRef

Stretcu, O.[Otilia], Vendrow, E.[Edward], Hata, K.[Kenji], Viswanathan, K.[Krishnamurthy], Ferrari, V.[Vittorio], Tavakkol, S.[Sasan], Zhou, W.[Wenlei], Avinash, A.[Aditya], Luo, E.[Enming], Alldrin, N.G.[Neil Gordon], Bateni, M.[MohammadHossein], Berger, G.[Gabriel], Bunner, A.[Andrew], Lu, C.T.[Chun-Ta], Rey, J.[Javier], DeSalvo, G.[Giulia], Krishna, R.[Ranjay], Fuxman, A.[Ariel],
Agile Modeling: From Concept to Classifier in Minutes,
ICCV23(22266-22277)
IEEE DOI 2401
BibRef

Xiangli, Y.B.[Yuan-Bo], Xu, L.N.[Lin-Ning], Pan, X.G.[Xin-Gang], Zhao, N.X.[Nan-Xuan], Dai, B.[Bo], Lin, D.[Dahua],
AssetField: Assets Mining and Reconfiguration in Ground Feature Plane Representation,
ICCV23(3228-3238)
IEEE DOI 2401
The unique objects found. BibRef

Yan, A.[An], Wang, Y.[Yu], Zhong, Y.[Yiwu], Dong, C.[Chengyu], He, Z.[Zexue], Lu, Y.J.[Yu-Jie], Wang, W.Y.[William Yang], Shang, J.[Jingbo], McAuley, J.[Julian],
Learning Concise and Descriptive Attributes for Visual Recognition,
ICCV23(3067-3077)
IEEE DOI 2401
BibRef

Gan, Z.[Zeyu], Zhao, S.[Suyun], Kang, J.L.[Jin-Long], Shang, L.Y.[Li-Yuan], Chen, H.[Hong], Li, C.P.[Cui-Ping],
Superclass Learning with Representation Enhancement,
CVPR23(24060-24069)
IEEE DOI 2309
BibRef

Tukra, S.[Samyakh], Hoffman, F.[Frederick], Chatfield, K.[Ken],
Improving Visual Representation Learning Through Perceptual Understanding,
CVPR23(14486-14495)
IEEE DOI 2309
BibRef

Zhang, Y.Z.[Yun-Zhi], Wu, S.Z.[Shang-Zhe], Snavely, N.[Noah], Wu, J.J.[Jia-Jun],
Seeing a Rose in Five Thousand Ways,
CVPR23(962-971)
IEEE DOI 2309
BibRef

Guo, X.B.[Xiao-Bo], Gao, N.[Neng], Wang, F.[Fali], Mu, N.[Nan], Wang, L.[Lei], Dong, Y.[Yao],
BEFSR: A Multiple Attention-Based Model Considering Bidirectional Entity Information Flows and Few-Shot Relations,
ICPR22(4441-4447)
IEEE DOI 2212
Aggregates, Knowledge based systems, Knowledge representation, Task analysis BibRef

Yang, X.Y.[Xing-Yi], Ye, J.W.[Jing-Wen], Wang, X.C.[Xin-Chao],
Factorizing Knowledge in Neural Networks,
ECCV22(XXXIV:73-91).
Springer DOI 2211
Assemble knowledge from networks, recast into factor networks. BibRef

Kamath, A.[Amita], Clark, C.[Christopher], Gupta, T.[Tanmay], Kolve, E.[Eric], Hoiem, D.[Derek], Kembhavi, A.[Aniruddha],
Webly Supervised Concept Expansion for General Purpose Vision Models,
ECCV22(XXXVI:662-681).
Springer DOI 2211
BibRef

Joshi, P.[Piyush], Rastegarpanah, A.[Alireza], Stolkin, R.[Rustam],
A Survey on Training Free 3D Texture-less Object Recognition Techniques,
DICTA20(1-3)
IEEE DOI 2201
Training, Image recognition, Cameras, Object recognition, Time factors, Robots, 3D object recognition, Feature descriptors BibRef

Zhang, Y.F.[Yi-Feng], Jiang, M.[Ming], Zhao, Q.[Qi],
Explicit Knowledge Incorporation for Visual Reasoning,
CVPR21(1356-1365)
IEEE DOI 2111
Knowledge engineering, Visualization, Semantics, Knowledge based systems, Cognition, Pattern recognition BibRef

Hong, X.[Xin], Lan, Y.Y.[Yan-Yan], Pang, L.[Liang], Guo, J.F.[Jia-Feng], Cheng, X.Q.[Xue-Qi],
Transformation Driven Visual Reasoning,
CVPR21(6899-6908)
IEEE DOI 2111
Visualization, Computational modeling, Cognition, Data models, Pattern recognition, Task analysis BibRef

Zheng, W.B.[Wen-Bo], Yan, L.[Lan], Wang, F.Y.[Fei-Yue], Gou, C.[Chao],
Progressive Knowledge-Embedded Unified Perceptual Parsing for Scene Understanding,
MULA21(1633-1642)
IEEE DOI 2109
Deep learning, Visualization, Organizations, Knowledge representation, Logic gates BibRef

Olague, G.[Gustavo], Olague, M.[Matthieu], Jacobo-Lopez, A.R.[Angel R.], Ibarra-Vázquez, G.[Gerardo],
Less is More: Pursuing the Visual Turing Test with the Kuleshov Effect,
AUVi21(1553-1561)
IEEE DOI 2109
Deep learning, Visualization, Image recognition, Psychology, Motion pictures BibRef

Belavadi, P.[Poornima], Burbach, L.[Laura], Ziefle, M.[Martina], Valdez, A.C.[André Calero],
Finding a Structure: Evaluating Different Modelling Languages Regarding Their Suitability of Designing Agent-Based Models,
DHM21(I:201-219).
Springer DOI 2108
BibRef

Mi, L.[Li], Chen, Z.Z.[Zhen-Zhong],
Hierarchical Graph Attention Network for Visual Relationship Detection,
CVPR20(13883-13892)
IEEE DOI 2008
Visualization, Semantics, Correlation, Feature extraction, Cognition, Task analysis, Proposals BibRef

Abbasnejad, E.[Ehsan], Abbasnejad, I.[Iman], Wu, Q.[Qi], Shi, J.[Javen], van den Hengel, A.J.[Anton J.],
Gold Seeker: Information Gain From Policy Distributions for Goal-Oriented Vision-and-Langauge Reasoning,
CVPR20(13447-13456)
IEEE DOI 2008
What information will be needed? Task analysis, Visualization, Learning (artificial intelligence), Training, History, Games BibRef

Zhao, H.S.[Heng-Shuang], Jia, J.Y.[Jia-Ya], Koltun, V.[Vladlen],
Exploring Self-Attention for Image Recognition,
CVPR20(10073-10082)
IEEE DOI 2008
Convolution, Image recognition, Computational modeling, Robustness, Tensile stress, Standards BibRef

Luo, G., Zhou, Y., Sun, X., Cao, L., Wu, C., Deng, C., Ji, R.,
Multi-Task Collaborative Network for Joint Referring Expression Comprehension and Segmentation,
CVPR20(10031-10040)
IEEE DOI 2008
Task analysis, Feature extraction, Frequency modulation, Visualization, Collaborative work, Tensile stress, Linguistics BibRef

Chen, Z., Wang, P., Ma, L., Wong, K.K., Wu, Q.,
Cops-Ref: A New Dataset and Task on Compositional Referring Expression Comprehension,
CVPR20(10083-10092)
IEEE DOI 2008
Cognition, Visualization, Task analysis, Cats, Engines, Semantics, Genetic expression BibRef

Liao, Y., Liu, S., Li, G., Wang, F., Chen, Y., Qian, C., Li, B.,
A Real-Time Cross-Modality Correlation Filtering Method for Referring Expression Comprehension,
CVPR20(10877-10886)
IEEE DOI 2008
Correlation, Feature extraction, Visualization, Proposals, Kernel, Heating systems, Filtering BibRef

Eum, S., Han, D., Briggs, G.,
SomethingFinder: Localizing undefined regions using referring expressions,
MVM20(1551-1554)
IEEE DOI 2008
Visualization, Image color analysis, Task analysis, Image resolution, Training, Complexity theory BibRef

Yang, S., Li, G., Yu, Y.,
Graph-Structured Referring Expression Reasoning in the Wild,
CVPR20(9949-9958)
IEEE DOI 2008
Cognition, Visualization, Semantics, Linguistics, Grounding, Layout, Image edge detection BibRef

Wicker, M.[Matthew], Kwiatkowska, M.[Marta],
Robustness of 3D Deep Learning in an Adversarial Setting,
CVPR19(11759-11767).
IEEE DOI 2002
Spatial arrangements. BibRef

Sun, D.W.[Da-Wei], Yao, A.[Anbang], Zhou, A.[Aojun], Zhao, H.[Hao],
Deeply-Supervised Knowledge Synergy,
CVPR19(6990-6999).
IEEE DOI 2002
BibRef

Wu, H.[Hao], Mao, J.Y.[Jia-Yuan], Zhang, Y.[Yufeng], Jiang, Y.N.[Yu-Ning], Li, L.[Lei], Sun, W.W.[Wei-Wei], Ma, W.Y.[Wei-Ying],
Unified Visual-Semantic Embeddings: Bridging Vision and Language With Structured Meaning Representations,
CVPR19(6602-6611).
IEEE DOI 2002
BibRef

Bucher, M.[Maxime], Herbin, S.[Stéphane], Jurie, F.[Frédéric],
Semantic Bottleneck for Computer Vision Tasks,
ACCV18(II:695-712).
Springer DOI 1906
BibRef

Wang, P.[Pei], Vasconcelos, N.M.[Nuno M.],
Towards Realistic Predictors,
ECCV18(XIII: 37-53).
Springer DOI 1810
Choose to work on the easier problems. BibRef

Groth, O.[Oliver], Fuchs, F.B.[Fabian B.], Posner, I.[Ingmar], Vedaldi, A.[Andrea],
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking,
ECCV18(I: 724-739).
Springer DOI 1810
BibRef

Nagarajan, T.[Tushar], Grauman, K.[Kristen],
Attributes as Operators: Factorizing Unseen Attribute-Object Compositions,
ECCV18(I: 172-190).
Springer DOI 1810
BibRef

Xiao, T.[Tete], Liu, Y.C.[Ying-Cheng], Zhou, B.[Bolei], Jiang, Y.N.[Yu-Ning], Sun, J.[Jian],
Unified Perceptual Parsing for Scene Understanding,
ECCV18(VI: 432-448).
Springer DOI 1810
BibRef

Zhang, J.J.[Jun-Jie], Wu, Q.[Qi], Shen, C.H.[Chun-Hua], Zhang, J.[Jian], Lu, J.F.[Jian-Feng], van den Hengel, A.J.[Anton J.],
Goal-Oriented Visual Question Generation via Intermediate Rewards,
ECCV18(VI: 189-204).
Springer DOI 1810
BibRef

Wang, H.[Hao], Lin, X.Y.[Xing-Yu], Zhang, Y.M.[Yi-Meng], Lee, T.S.[Tai Sing],
Learning Robust Object Recognition Using Composed Scenes from Generative Models,
CRV17(232-239)
IEEE DOI 1804
convolution, feature extraction, feedforward neural nets, image classification, image representation, visual cortex BibRef

Ramakrisnan, P.[Prasanna], Jaafar, A.[Azizah],
Motivation Design Methodology for Online Knowledge Sharing Interface,
IVIC17(224-232).
Springer DOI 1711
BibRef

Ali, A.R.[Afsheen Rafaqat], Shahid, U.[Usman], Ali, M.[Mohsen], Ho, J.[Jeffrey],
High-Level Concepts for Affective Understanding of Images,
WACV17(679-687)
IEEE DOI 1609
Analytical models, Feature extraction, Information technology, Multimedia communication, Neural networks, Predictive models, Support, vector, machines BibRef

de Souza, F.D.M.[Fillipe D. M.], Sarkar, S.[Sudeep], Cámara-Chávez, G.[Guillermo],
Building semantic understanding beyond deep learning from sound and vision,
ICPR16(2097-2102)
IEEE DOI 1705
Computational modeling, Feature extraction, Generators, Histograms, Semantics, Support vector machines, Visualization BibRef

Schwarz, K.[Katharina], Berg, T.L.[Tamara L.], Lensch, H.P.A.[Hendrik P. A.],
Auto-Illustrating Poems and Songs with Style,
ACCV16(IV: 87-103).
Springer DOI 1704
Large image dataset for selection. BibRef

Mottaghi, R.[Roozbeh], Hajishirzi, H.[Hannaneh], Farhadi, A.[Ali],
A Task-Oriented Approach for Cost-Sensitive Recognition,
CVPR16(2203-2211)
IEEE DOI 1612
BibRef

Ionescu, R.T.[Radu Tudor], Alexe, B.[Bogdan], Leordeanu, M.[Marius], Popescu, M.[Marius], Papadopoulos, D.P.[Dim P.], Ferrari, V.[Vittorio],
How Hard Can It Be? Estimating the Difficulty of Visual Search in an Image,
CVPR16(2157-2166)
IEEE DOI 1612
Human response time data. BibRef

Wu, Q.[Qi], Shen, C.H.[Chun-Hua], Liu, L.Q.[Ling-Qiao], Dick, A.[Anthony], van den Hengel, A.J.[Anton J.],
What Value Do Explicit High Level Concepts Have in Vision to Language Problems?,
CVPR16(203-212)
IEEE DOI 1612
Vision to language. BibRef

Mao, J.H.[Jun-Hua], Huang, J.[Jonathan], Toshev, A.[Alexander], Camburu, O.[Oana], Yuille, A.L.[Alan L.], Murphy, K.[Kevin],
Generation and Comprehension of Unambiguous Object Descriptions,
CVPR16(11-20)
IEEE DOI 1612
BibRef

Lu, C.[Cewu], Krishna, R.[Ranjay], Bernstein, M.[Michael], Fei-Fei, L.[Li],
Visual Relationship Detection with Language Priors,
ECCV16(I: 852-869).
Springer DOI 1611
Relationships identify objects. BibRef

Yu, L.C.[Li-Cheng], Poirson, P.[Patrick], Yang, S.[Shan], Berg, A.C.[Alexander C.], Berg, T.L.[Tamara L.],
Modeling Context in Referring Expressions,
ECCV16(II: 69-85).
Springer DOI 1611
How to refer to objects. BibRef

Mbock, E.A.M.[Etienne Aubin Mbe],
Image reconstruction using the reconfiguration technique,
AIPR15(1-9)
IEEE DOI 1605
feature extraction BibRef

Klarin, K., Celar, S.,
Modeling information resources and application using ontological engineering,
ICCVIA15(1-6)
IEEE DOI 1603
ontologies (artificial intelligence) BibRef

Sun, C.[Chen], Gan, C.[Chuang], Nevatia, R.[Ram],
Automatic Concept Discovery from Parallel Text and Visual Corpora,
ICCV15(2596-2604)
IEEE DOI 1602
Bicycles; Detectors; Roads; Semantics; Visualization; Vocabulary BibRef

de Lima, G.V.L.[Geovana V. L.], Castilho, T.R.[Thullyo R.], Bugatti, P.H.[Pedro H.], Saito, P.T.M.[Priscila T.M.], Lopes, F.M.[Fabrício M.],
A Complex Network-Based Approach to the Analysis and Classification of Images,
CIARP15(322-330).
Springer DOI 1511
Knowledge from multiple areas. BibRef

Savva, M.[Manolis], Chang, A.X.[Angel X.], Hanrahan, P.[Pat],
Semantically-enriched 3D models for common-sense knowledge,
Cognition15(24-31)
IEEE DOI 1510
Computational modeling. Physical properties connect to 3D models. BibRef

Zhu, Y.X.[Yi-Xin], Zhao, Y.B.[Yi-Biao], Zhu, S.C.[Song-Chun],
Understanding tools: Task-oriented object modeling, learning and recognition,
CVPR15(2855-2864)
IEEE DOI 1510
Tools such as hammer or brush. BibRef

Santos-Saavedra, D., Pardo, X.M., Iglesias, R., Canedo-Rodríguez, A., Álvarez-Santos, V.,
Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics,
IbPRIA15(130-137).
Springer DOI 1506
combination of an holistic representation and local information. BibRef

Ioannidou, A.[Anastasia], Chatzilari, E.[Elisavet], Nikolopoulos, S.[Spiros], Kompatsiaris, I.[Ioannis],
3D ResNets for 3D Object Classification,
MMMod19(I:495-506).
Springer DOI 1901
BibRef

Chantas, G.[Giannis], Kitsikidis, A.[Alexandros], Nikolopoulos, S.[Spiros], Dimitropoulos, K.[Kosmas], Douka, S.[Stella], Kompatsiaris, I.[Ioannis], Grammalidis, N.[Nikos],
Multi-Entity Bayesian Networks for Knowledge-Driven Analysis of ICH Content,
CVONT14(355-369).
Springer DOI 1504
Intangible Cultural Heritage BibRef

Kadar, I.[Ilan], Ben-Shahar, O.[Ohad],
SceneNet: A Perceptual Ontology for Scene Understanding,
CVONT14(385-400).
Springer DOI 1504
BibRef

Tasli, H.E.[H. Emrah], Sicre, R.[Ronan], Gevers, T.[Theo], Alatan, A.A.[A. Aydin],
Geometry-constrained spatial pyramid adaptation for image classification,
ICIP14(1051-1055)
IEEE DOI 1502
Color BibRef

Khosla, A.[Aditya], An, B.[Byoungkwon], Lim, J.J.[Joseph J.], Torralba, A.B.[Antonio B.],
Looking Beyond the Visible Scene,
CVPR14(3710-3717)
IEEE DOI 1409
Analyze the environment in the urban scene, crime, what may be near, etc. BibRef

Divvala, S.K.[Santosh K.], Farhadi, A.[Ali], Guestrin, C.[Carlos],
Learning Everything about Anything: Webly-Supervised Visual Concept Learning,
CVPR14(3270-3277)
IEEE DOI 1409
BibRef

Ordonez, V.[Vicente], Berg, T.L.[Tamara L.],
Learning High-Level Judgments of Urban Perception,
ECCV14(VI: 494-510).
Springer DOI 1408
urban perception judgments for wealth, uniqueness, and safety. BibRef

Martinez-Enriquez, A.M., Escalada-Imaz, G., Muhammad, A.[Aslam],
Problem Solving Environment Based on Knowledge Based System Principles,
MCPR14(81-91).
Springer DOI 1407
BibRef

Chen, Z.C.[Zi-Chong], Yang, F.[Feng], Lindner, A.[Albrecht], Barrenetxea, G.[Guillermo], Vetterli, M.[Martin],
How is the weather: Automatic inference from images,
ICIP12(1853-1856).
IEEE DOI 1302
BibRef

Steinberg, D.M.[Daniel M.], Pizarro, O.[Oscar], Williams, S.B.[Stefan B.],
Synergistic Clustering of Image and Segment Descriptors for Unsupervised Scene Understanding,
ICCV13(3463-3470)
IEEE DOI 1403
Scene understanding BibRef

Saleh, B.[Babak], Farhadi, A.[Ali], Elgammal, A.M.[Ahmed M.],
Object-Centric Anomaly Detection by Attribute-Based Reasoning,
CVPR13(787-794)
IEEE DOI 1309
In an image, not actions. BibRef

Juneja, M.[Mayank], Vedaldi, A.[Andrea], Jawahar, C.V., Zisserman, A.[Andrew],
Blocks That Shout: Distinctive Parts for Scene Classification,
CVPR13(923-930)
IEEE DOI 1309
Scene Classification BibRef

Chen, J.J.[Jing-Jing], Cao, X.C.[Xiao-Chun], Zhang, B.[Bao],
Object clique representation for scene classification,
ICPR12(2829-2832).
WWW Link. 1302
BibRef

Fornoni, M.[Marco], Caputo, B.[Barbara],
Scene Recognition with Naive Bayes Non-linear Learning,
ICPR14(3404-3409)
IEEE DOI 1412
BibRef
Earlier:
Indoor Scene Recognition using Task and Saliency-driven Feature Pooling,
BMVC12(98).
DOI Link 1301
Feature extraction BibRef

Liu, Y.X.[Yi-Xian], Hao, P.W.[Peng-Wei], Izquierdo, E.[Ebroul],
Stage-based 3D scene reconstruction from single image,
ICPR12(1034-1037).
WWW Link. 1302
BibRef
Earlier:
Scene geometric recognition from monocular image,
3DTV12(1-4).
IEEE DOI 1212
BibRef

Jiang, Y.N.[Yu-Ning], Yuan, J.S.[Jun-Song], Yu, G.[Gang],
Randomized Spatial Partition for Scene Recognition,
ECCV12(II: 730-743).
Springer DOI 1210
how to use spatial info BibRef

Ji, C.J.[Chuan-Jun], Zhou, X.D.[Xiang-Dong], Lin, L.[Lan], Yang, W.D.[Wei-Dong],
Labeling Images by Integrating Sparse Multiple Distance Learning and Semantic Context Modeling,
ECCV12(IV: 688-701).
Springer DOI 1210
BibRef

Kwitt, R.[Roland], Vasconcelos, N.M.[Nuno M.], Rasiwasia, N.[Nikhil],
Scene Recognition on the Semantic Manifold,
ECCV12(IV: 359-372).
Springer DOI 1210
Scene category. BibRef

Redi, M.[Miriam], Merialdo, B.[Bernard],
Enhancing Semantic Features with Compositional Analysis for Scene Recognition,
Concept12(III: 446-455).
Springer DOI 1210
BibRef

Parizi, S.N.[Sobhan Naderi], Oberlin, J.G.[John G.], Felzenszwalb, P.F.[Pedro F.],
Reconfigurable models for scene recognition,
CVPR12(2775-2782).
IEEE DOI 1208
BibRef

Yu, X.D.[Xiao-Dong], Fermuller, C.[Cornelia], Teo, C.L.[Ching Lik], Yang, Y.Z.[Ye-Zhou], Aloimonos, Y.[Yiannis],
Active scene recognition with vision and language,
ICCV11(810-817).
IEEE DOI 1201
Use high-level knowledge for recognition. BibRef

Möller, B.[Birgit], Greß, O.[Oliver], Posch, S.[Stefan],
Knowing What Happened: Automatic Documentation of Image Analysis Processes,
CVS11(1-10).
Springer DOI 1109
BibRef

Sherrah, J.[Jamie],
Learning to Adapt: A Method for Automatic Tuning of Algorithm Parameters,
ACIVS10(I: 414-425).
Springer DOI 1012
BibRef

Kulikowski, J.L.[Juliusz L.],
Ontological Models as Tools for Image Content Understanding,
ICCVG10(I: 43-58).
Springer DOI 1009
BibRef

Wang, G.[Gang], Gallagher, A.C.[Andrew C.], Luo, J.B.[Jie-Bo], Forsyth, D.A.[David A.],
Seeing People in Social Context: Recognizing People and Social Relationships,
ECCV10(V: 169-182).
Springer DOI 1009
Familial social relationships to recognize people, and to recognize such relationships from image. BibRef

Satkin, S.[Scott], Hebert, M.[Martial],
3DNN: Viewpoint Invariant 3D Geometry Matching for Scene Understanding,
ICCV13(1873-1880)
IEEE DOI 1403
3D Data BibRef

Satkin, S.[Scott], Lin, J.[Jason], Hebert, M.[Martial],
Data-Driven Scene Understanding from 3D Models,
BMVC12(128).
DOI Link 1301
BibRef

Gupta, A.[Abhinav], Satkin, S.[Scott], Efros, A.A.[Alexei A.], Hebert, M.[Martial],
From 3D scene geometry to human workspace,
CVPR11(1961-1968).
IEEE DOI 1106
BibRef

Gupta, A.[Abhinav], Efros, A.A.[Alexei A.], Hebert, M.[Martial],
Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics,
ECCV10(IV: 482-496).
Springer DOI
WWW Link. 1009
Award, ECCV, HM. Reason about the scene in 3D, objects have volume and 3d relationships. BibRef

Gao, T.S.[Tian-Shi], Koller, D.[Daphne],
Discriminative learning of relaxed hierarchy for large-scale visual recognition,
ICCV11(2072-2079).
IEEE DOI 1201
Really need thousands of categories for real world. Multiclass classifier, hierarchical. BibRef

Wang, H.Y.[Hua-Yan], Gould, S.[Stephen], Koller, D.[Daphne],
Discriminative Learning with Latent Variables for Cluttered Indoor Scene Understanding,
CACM(56), No. 4, April 2013, pp. 92-99.
DOI Link 1304
BibRef
Earlier: ECCV10(II: 435-449).
Springer DOI 1009
BibRef
And: ECCV10(IV: 497-510).
Springer DOI 1009
We address the problem of understanding an indoor scene from a single image in terms of recovering the room geometry (floor, ceiling, and walls) and furniture layout. Explain the scene by the object face and the clutter (i.e. what is on top of the desk) BibRef