13.6.6 Recognition by Function, By Use, Affordance

di Manzo, M., Trucco, E., Giunchiglia, F., and Ricci, F.,
FUR: Understanding FUnctional Reasoning,
IJIS(4), 1989, pp. 431-457. BibRef 8900

di Manzo, M., Adorni, G., Giunchiglia, F.,
Reasoning about Scene Descriptions,
PIEEE(74), 1986, pp. 1013-1025. BibRef 8600

Stark, L.,
Functionality in Object Recognition,
CVIU(62), No. 2, September 1995, pp. 145-146.
DOI Link Review, introduction to the special issue. BibRef 9509

Stark, L., Bowyer, K.W.,
Achieving Generalized Object Recognition Through Reasoning About Association of Function to Structure,
PAMI(13), No. 10, October 1991, pp. 1097-1104.
IEEE DOI BibRef 9110

Stark, L.[Louise],
Reasoning About Functionality In Object Recognition,
IVC(16), No. 11, August 1 1998, pp. 727-728.
Elsevier DOI 9808
Special issue Introduction. BibRef

Stark, L., and Bowyer, K.W.,
Function-Based Generic Recognition for Multiple Object Categories,
CVGIP(59), No. 1, January 1994, pp. 1-21.
DOI Link BibRef 9401
And: 3DORS93(447-470). BibRef
Earlier:
Generic Recognition Through Qualitative Reasoning about 3-D Shape and Object Function,
CVPR91(251-256).
IEEE DOI 3-D wireframe models of objects and a comparison with the results of human recognition. Model matching with constraints to infer functionality. BibRef

Stark, L., and Bowyer, K.W.,
Indexing Function-Based Categories for Generic Recognition,
CVPR92(795-797).
IEEE DOI Functional use rather than shape (chair is for sitting on). BibRef 9200

Sutton, M.A.[Melanie A.], Stark, L.[Louise], Bowyer, K.W.[Kevin W.],
Function from Visual Analysis and Physical Interaction: A Methodology for Recognition of Generic Classes of Objects,
IVC(16), No. 11, August 1 1998, pp. 745-763.
Elsevier DOI 9808
BibRef

Sutton, M.A.[Melanie A.],
Function from Visual Analysis and Physical Interaction: A Methodology for Recognition of Generic Classes of Objects,
Ph.D.Thesis, Univ. of South FL, May, 1997. BibRef 9705

Sutton, M.A.[Melanie A.], Stark, L., Bowyer, K.W.,
GRUFF-3: Generalizing the Domain of a Function-Based Recognition System,
PR(27), No. 12, December 1994, pp. 1743-1766.
Elsevier DOI Generic objects. Form and function. BibRef 9412

Woods, K., Cook, D., Hall, L.O., Bowyer, K.W., and Stark, L.,
Learning Membership Functions in a Function-Based Object Recognition System,
JAIR(3), 1995, pp. 187-222.
HTML Version. (postscript: volume3/woods95a.ps) BibRef 9500

Cook, D., Hall, L.O., Stark, L., Bowyer, K.W.,
Learning Combination of Evidence Functions in Object Recognition,
AAAI-MLCV93(xx). University of South Florida. BibRef 9300

Green, K., Eggert, D.W., Stark, L., Bowyer, K.W.,
Generic Recognition of Articulated Objects Through Reasoning about Potential Function,
CVIU(62), No. 2, September 1995, pp. 177-193.
DOI Link BibRef 9509
Earlier:
Generic Recognition of Articulated Objects by Reasoning about Functionality,
ICPR94(A:847-849).
IEEE DOI Articulated Shape. Objects are categorized according to potential uses. First recover an articulated shape model, determine functional potential BibRef

Stark, L., and Bowyer, K.W.,
Generic Object Recognition Using Form and Function,
World Scientific1996. ISBN 981-02-1508-8. BibRef 9600

Stark, L.[Louise],
Functional Context In Vision,
Context95(xx) BibRef 9500

Stark, L.,
Recognizing Object Function Through Reasoning About 3-D Shape and Dynamic Physical Properties,
CVPR94(546-553).
IEEE DOI BibRef 9400

Stark, L., Hall, L.O., Bowyer, K.W.,
Methods for Combination of Evidence in Function-Based 3-D Object Recognition,
PRAI(7), No. 3, June 1993, pp. 573-594. BibRef 9306

Stark, L., Bowyer, K.W., Hoover, A., Goldgof, D.B.,
Recognizing Object Function Through Reasoning about Partial Shape Descriptions and Dynamic Physical-Properties,
PIEEE(84), No. 11, November 1996, pp. 1640-1656. 9611
BibRef

Stark, L., Hoover, A.W., Goldgof, D.B., Bowyer, K.W.,
Function-Based Recognition from Incomplete Knowledge of Shape,
WQV93(11-22). BibRef 9300
And:
Function-Based Recognition from Incomplete Knowledge of Object Shape,
Function93(141-148). BibRef

Vaina, L.M.[Lucia M.], and Jaulent, M.C.,
Object Structure and Action Requirements: A Compatibility Model for Functional Recognition,
IJIS(6), 1991, pp. 313-336. BibRef 9100

Hodges, J.,
Functional and Physical Object Characteristics and Object Recognition in Improvisation,
CVIU(62), No. 2, September 1995, pp. 147-163.
DOI Link BibRef 9509
And:
Naive Mechanics: A Computational Model of Device Use and Function in Design Improvement,
IEEE_Expert(7), 1992, pp. 14-27. Issues of how to determine constraints of a situation in order to use an object. BibRef

Bogoni, L., Bajcsy, R.,
Interactive Recognition and Representation of Functionality,
CVIU(62), No. 2, September 1995, pp. 194-214.
DOI Link BibRef 9509
And:
Active Investigation of Functionality,
WVB94(xx). Function implies action, the representation includes intrinsic properties along with functions (how it is used) properties. Focuses on manipulations. BibRef

Bogoni, L., Rucci, M., Bajcsy, R.,
Investigating Functionality: The Case of Piercing Operation,
ICPR94(A:837-839).
IEEE DOI BibRef 9400

Bogoni, L.[Luca],
Functional Features for Chopping Extracted from Observations and Interactions,
IVC(16), No. 11, August 1 1998, pp. 765-783.
Elsevier DOI 9808
BibRef

Cooper, P.R., Birnbaum, L.A., Brand, M.E.,
Causal Scene Understanding,
CVIU(62), No. 2, September 1995, pp. 215-231.
DOI Link BibRef 9509
Earlier: A2, A3, A1:
Using Causal Scene Analysis to Direct Focus of Attention,
WQV93(23-32). Includes reasoning about what will happen and why (blocks domain, elementary physics). BibRef

Brand, M.E., Birnbaum, L.A., Cooper, P.R.,
Sensible Scenes: Visual Understanding of Complex Scenes Through Causal Analysis,
AAAI-93(xx-yy). BibRef 9300

Birnbaum, L.A., Brand, M.E., and Cooper, P.R.[Paul R.],
Looking for Trouble: Using Causal Semantics to Direct Focus of Attention,
ICCV93(49-56).
IEEE DOI Focus of Attention. Adding rules of where to look to generate scan patterns like humans. BibRef 9300

Brand, M.E., Cooper, P.R., Birnbaum, L.A.,
Seeing Physics or, Physics Is for Prediction,
PBMCV95(SESSION 5) BibRef 9500

Brand, M.E.,
Physics-Based Visual Understanding,
CVIU(65), No. 2, February 1997, pp. 192-205.
DOI Link 9704
BibRef

Duric, Z., Fayman, J.A., Rivlin, E.,
Function from Motion,
PAMI(18), No. 6, June 1996, pp. 579-591.
IEEE DOI 9607
BibRef
Earlier:
Recognizing Functionality,
SCV95(247-252).
IEEE DOI Optical Flow. U. of Maryland. Israel Inst. of Technology. Function from motion. Recognition of different actions (slicing, chopping) based on an analysis of optical flow. BibRef

Caruthers, F.,
Recognizing Object Function Through Reasoning About Partial Shape Descriptions and Dynamic Physical-Properties,
PIEEE(84), No. 11, November 1996, pp. 1638-1639. 9611

See also Recognizing Object Function Through Reasoning about Partial Shape Descriptions and Dynamic Physical-Properties. BibRef

Hassanin, M.[Mohammed], Khan, S.[Salman], Tahtali, M.[Murat],
Visual Affordance and Function Understanding: A Survey,
Surveys(54), No. 3, April 2021, pp. xx-yy.
DOI Link 2106
Survey, Visual Function. Discover information, understand it, and interact with the environment. deep learning, Affordance prediction, functional scene understanding, visual reasoning BibRef

Zhai, W.[Wei], Luo, H.C.[Hong-Chen], Zhang, J.[Jing], Cao, Y.[Yang], Tao, D.C.[Da-Cheng],
One-Shot Object Affordance Detection in the Wild,
IJCV(130), No. 10, October 2022, pp. 2472-2500.
Springer DOI 2209
Dataset, Affordance.
WWW Link. Affordance: potential action possibilities of objects in the scene. BibRef

Chen, D.P.[Dong-Pan], Kong, D.[Dehui], Li, J.H.[Jing-Hua], Wang, L.C.[Li-Chun], Gao, J.[Junna], Yin, B.C.[Bao-Cai],
OASNet: Object Affordance State Recognition Network With Joint Visual Features and Relational Semantic Embeddings,
CirSysVideo(34), No. 5, May 2024, pp. 3368-3382.
IEEE DOI Code:
WWW Link. 2405
Task analysis, Affordances, Image recognition, Semantics, Visualization, Transformers, Robots BibRef

Li, G.[Gen], Sun, D.Q.[De-Qing], Sevilla-Lara, L.[Laura], Jampani, V.[Varun],
One-Shot Open Affordance Learning with Foundation Models,
CVPR24(3086-3096)
IEEE DOI Code:
WWW Link. 2410
Visualization, Affordances, Training data, Benchmark testing, Data models, Foundation Models, Vision-Language Models BibRef

Delitzas, A.[Alexandros], Takmaz, A.[Ayça], Tombari, F.[Federico], Sumner, R.[Robert], Pollefeys, M.[Marc], Engelmann, F.[Francis],
SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes,
CVPR24(14531-14542)
IEEE DOI 2410
Grounding, Annotations, Affordances, Motion segmentation, Motion estimation, Natural languages, 3D scene understanding, motion estimation BibRef

Wang, X.H.[Xiao-Han], Liu, Y.H.[Yue-Hu], Song, X.H.[Xin-Hang], Liu, Y.[Yuyi], Zhang, S.[Sixian], Jiang, S.Q.[Shu-Qiang],
An Interactive Navigation Method with Effect-oriented Affordance,
CVPR24(16446-16456)
IEEE DOI 2410
Visualization, Uncertainty, Costs, Navigation, Affordances, Reinforcement learning, Embodied AI, affordance, Interactive Navigation BibRef

Chen, S.Z.[Shi-Zhe], Garcia, R.[Ricardo], Laptev, I.[Ivan], Schmid, C.[Cordelia],
SUGAR: Pre-training 3D Visual Representations for Robotics,
CVPR24(18049-18060)
IEEE DOI 2410
Representation learning, Visualization, Solid modeling, Grounding, Affordances, Semantics BibRef

Rai, A.[Arushi], Buettner, K.[Kyle], Kovashka, A.[Adriana],
Strategies to Leverage Foundational Model Knowledge in Object Affordance Grounding,
WhatNext24(1714-1723)
IEEE DOI 2410
Heating systems, Grounding, Affordances, Pipelines BibRef

Cuttano, C.[Claudia], Rosi, G.[Gabriele], Trivigno, G.[Gabriele], Averta, G.[Giuseppe],
What does CLIP know about peeling a banana?,
Reasoning24(2238-2247)
IEEE DOI 2410
Training, Affordances, Scalability, Computational modeling, Supervised learning BibRef

Liang, Y.Z.[Yuan-Zhi], Wang, X.H.[Xiao-Han], Zhu, L.C.[Lin-Chao], Yang, Y.[Yi],
MAAL: Multimodality-Aware Autoencoder-based Affordance Learning for 3D Articulated Objects,
ICCV23(217-227)
IEEE DOI 2401
BibRef

Tang, J.J.[Jia-Jin], Zheng, G.[Ge], Yu, J.Y.[Jing-Yi], Yang, S.[Sibei],
CoTDet: Affordance Knowledge Prompting for Task Driven Object Detection,
ICCV23(3045-3055)
IEEE DOI 2401
BibRef

Wu, R.[Ruihai], Ning, C.[Chuanruo], Dong, H.[Hao],
Learning Foresightful Dense Visual Affordance for Deformable Object Manipulation,
ICCV23(10913-10922)
IEEE DOI Code:
WWW Link. 2401
BibRef

Khalifa, Z.[Zeyad], Shah, S.A.A.[Syed Afaq Ali],
A Large Scale Multi-View RGBD Visual Affordance Learning Dataset,
ICIP23(1325-1329)
IEEE DOI Code:
WWW Link. 2312
BibRef

Singhal, A.[Anirudh], Chopra, A.[Ayush], Ayush, K.[Kumar], Patel, U.[Utkarsh], Krishnamurthy, B.[Balaji],
Towards a Unified Framework for Visual Compatibility Prediction,
WACV20(3596-3605)
IEEE DOI 2006
Task analysis, Visualization, Robustness, Feature extraction, Context modeling, Standards, Sensitivity BibRef

Zhang, L.Z.[Ling-Zhi], Du, W.Y.[Wei-Yu], Zhou, S.H.[Sheng-Hao], Wang, J.C.[Jian-Cong], Shi, J.B.[Jian-Bo],
Inpaint2Learn: A Self-Supervised Framework for Affordance Learning,
WACV22(3778-3787)
IEEE DOI 2202
Training, Affordances, Pipelines, Predictive models, Benchmark testing, Adversarial machine learning, Analysis and Understanding Scene Understanding BibRef

Minh, C.N.D.[Chau Nguyen Duc], Gilani, S.Z.[Syed Zulqarnain], Islam, S.M.S.[Syed Mohammed Shamsul], Suter, D.[David],
Learning Affordance Segmentation: An Investigative Study,
DICTA20(1-8)
IEEE DOI 2201
Properties, capabilities. Image segmentation, Visualization, Affordances, Supervised learning, Semantics, Feature extraction, Task analysis BibRef

Thermos, S.[Spyridon], Papadopoulos, G.T.[Georgios T.], Daras, P.[Petros], Potamianos, G.[Gerasimos],
Attention-Enhanced Sensorimotor Object Recognition,
ICIP18(336-340)
IEEE DOI 1809
BibRef
Earlier:
Deep Affordance-Grounded Sensorimotor Object Recognition,
CVPR17(49-57)
IEEE DOI 1711
Object recognition, Measurement, Feature extraction, Task analysis, Predictive models, Entropy, Dispersion, deep neural networks. Biological neural networks, Robot sensing systems, Visualization BibRef

Sawatzky, J.[Johann], Garbade, M.[Martin], Gall, J.[Juergen],
Ex Paucis Plura: Learning Affordance Segmentation from Very Few Examples,
GCPR18(169-184).
Springer DOI 1905
Use existing annotated datasets to annotate new ones (reduce what needs more work). BibRef

Lüddecke, T.[Timo], Wörgötter, F.[Florentin],
Learning to Segment Affordances,
AutoRob17(769-776)
IEEE DOI 1802
Computer architecture, Cost function, Image segmentation, Predictive models, Training BibRef

Hassan, M.[Mahmudul], Dharmaratne, A.[Anuja],
'Affordance' detection by mid-level physical parts,
ICVNZ15(1-6)
IEEE DOI 1701
functional classification of objects. computer vision BibRef

Chao, Y.W.[Yu-Wei], Wang, Z.[Zhan], Mihalcea, R.[Rada], Deng, J.[Jia],
Mining semantic affordances of visual object categories,
CVPR15(4259-4267)
IEEE DOI 1510
BibRef

Ku, L.Y.[Li Yang], Sen, S.[Shiraj], Learned-Miller, E.G.[Erik G.], Grupen, R.A.[Roderic A.],
The Aspect Transition Graph: An Affordance-Based Model,
Affordance14(459-465).
Springer DOI 1504
BibRef

Grabner, H.[Helmut], Gall, J.[Juergen], Van Gool, L.J.[Luc J.],
What makes a chair a chair?,
CVPR11(1529-1536).
IEEE DOI 1106
BibRef

Goh, T.[Taeil], West, R.[Ryan], Okada, K.[Kazunori],
Robust detection of semantically equivalent visually dissimilar objects,
SLAM08(1-8).
IEEE DOI 0806
BibRef

Bar-Aviv, E., Rivlin, E.,
Functional 3D Object Classification Using Simulation of Embodied Agent,
BMVC06(I:307).
PDF File. 0609
BibRef

Narayanan, N.H., Chandrasekaran, B.,
Reasoning Visually about Spatial Interactions,
IJCAI91(360-365). BibRef 9100

Kise, K., Hattori, H., Kitahashi, T., and Fukunaga, K.,
Representing and Recognizing Simple Hand-Tools Based on Their Functions,
ACCV93(656-659). BibRef 9300

Ho, S.,
Representing and Using Functional Definitions for Visual Recognition,
Ph.D.Thesis, Univ. of Wisconsin, 1987. BibRef 8700

Bobick, A.F.[Aaron F.], Richards, W.A.[Whitman A.],
Classifying Objects from Visual Information,
MIT AI Memo-879, June 1986.
WWW Link. BibRef 8606

Bobick, A.F.[Aaron F.],
Natural Object Categorization,
MIT AI-TR-1001, November 1987.
WWW Link. BibRef 8711

Lowry, M.R.,
Algorithm Synthesis for IU Applications,
DARPA87(835-842). BibRef 8700

Lowry, M.R.,
Reasoning between Structure and Function,
DARPA82(260-264). BibRef 8200

Freeman, P., and Newell, A.,
A Model for Functional Reasoning in Design,
IJCAI71(621-640). Not vision, but function analysis. BibRef 7100

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Integration of Vision Modules, Select Operations, Sequence Operations .