7.1.7.11 Generic Object Detection, Open World, Open-Set, Open-Vocabulary

Chapter Contents (Back)
Generic Objects. Open-Set Objects.
See also Region of Interest Detection, ROI.
See also Instance of Particular Object, Specified Object.
See also Dense Object Detection.

Mikolajczyk, K.[Krystian], Tuytelaars, T.[Tinne], Schmid, C., Zisserman, A., Matas, J.G., Schaffalitzky, F., Kadir, T., Van Gool, L.J.,
A Comparison of Affine Region Detectors,
IJCV(65), No. 1-2, November 2005, pp. 43-72.
Springer DOI 0604
Six types of detectors are included: detectors based on affine normalization around Harris (
See also Scale and Affine Invariant Interest Point Detectors. ); (
See also Automated location matching in movies. ) and Hessian points (
See also Scale and Affine Invariant Interest Point Detectors. ), MSER: Maximally stable extremal regions (
See also Robust Wide Baseline Stereo from Maximally Stable Extremal Regions. ); an edge-based region detector (Tuytelaars and Van Gool, 1999) and Intensity extrema (
See also Matching Widely Separated Views Based on Affine Invariant Regions. ), Salient regions (
See also Affine Invariant Salient Region Detector, An. ). BibRef

Seo, H.J.[Hae Jong], Milanfar, P.[Peyman],
Training-Free, Generic Object Detection Using Locally Adaptive Regression Kernels,
PAMI(32), No. 9, September 2010, pp. 1688-1704.
IEEE DOI 1008
BibRef
Earlier:
Using local regression kernels for statistical object detection,
ICIP08(2380-2383).
IEEE DOI 0810
Detection-locaization to search without training. Single example of the object of interest to find similar matches. Local regression kernels. BibRef

Alexe, B.[Bogdan], Deselaers, T.[Thomas], Ferrari, V.[Vittorio],
Measuring the Objectness of Image Windows,
PAMI(34), No. 11, November 2012, pp. 2189-2202.
IEEE DOI 1209
BibRef
Earlier:
What is an object?,
CVPR10(73-80).
IEEE DOI 1006
BibRef
And:
ClassCut for Unsupervised Class Segmentation,
ECCV10(V: 380-393).
Springer DOI 1009
BibRef
And: A2, A1, A3:
Localizing Objects While Learning Their Appearance,
ECCV10(IV: 452-466).
Springer DOI 1009
Does an image window contain an object (any object). A generic object measure. Objects with well defined boundaries vs. amorphous background elements. BibRef

Deselaers, T.[Thomas], Ferrari, V.[Vittorio],
Visual and semantic similarity in ImageNet,
CVPR11(1777-1784).
IEEE DOI 1106
BibRef
Earlier:
Global and efficient self-similarity for object classification and detection,
CVPR10(1633-1640).
IEEE DOI Video of talk:
WWW Link. 1006
BibRef

Deselaers, T.[Thomas], Alexe, B.[Bogdan], Ferrari, V.[Vittorio],
Weakly Supervised Localization and Learning with Generic Knowledge,
IJCV(100), No. 3, December 2012, pp. 275-293.
WWW Link. 1210
BibRef

Pan, H.[Hong], Zhu, Y.P.[Ya-Ping], Xia, L.Z.[Liang-Zheng],
Efficient and accurate face detection using heterogeneous feature descriptors and feature selection,
CVIU(117), No. 1, January 2013, pp. 12-28.
Elsevier DOI 1212
BibRef
Earlier:
Fusing multi-feature representation and PSO-Adaboost based feature selection for reliable frontal face detection,
ICIP13(2998-3002)
IEEE DOI 1402
Cascade classifiers Face detection; PSO; Adaboost; Feature selection; Cascade classifier BibRef

Pan, H.[Hong], Zhu, Y.P.[Ya-Ping], Qin, A.K., Xia, L.Z.[Liang-Zheng],
Mining heterogeneous class-specific codebook for categorical object detection and classification,
ICIP13(3132-3136)
IEEE DOI 1402
Class-specific codebook BibRef

Pan, H.[Hong], Olsen, S.I.[S°ren Ingvor], Zhu, Y.P.[Ya-Ping],
Feature representation of RGB-D images using joint spatial-depth feature pooling,
PRL(80), No. 1, 2016, pp. 239-248.
Elsevier DOI 1609
BibRef
Earlier:
Object classification from RGB-D images using depth context kernel descriptors,
ICIP15(512-516)
IEEE DOI 1512
BibRef
Earlier:
Joint Spatial-Depth Feature Pooling for RGB-D Object Classification,
SCIA15(314-326).
Springer DOI 1506
BibRef
Earlier:
Object Classification and Detection with Context Kernel Descriptors,
CIARP14(827-835).
Springer DOI 1411
RGB-D feature representation. Context cue BibRef

Pan, H.[Hong], Zhu, Y.P.[Ya-Ping], Xia, S.[Siyu], Qin, K.[Kai],
Improved generic categorical object detection fusing depth cue with 2D appearance and shape features,
ICPR12(1467-1470).
WWW Link. 1302
BibRef

Pan, H.[Hong], Xia, L.Z.[Liang-Zheng], Nguyen, T.Q.[Truong Q.],
Robust object detection scheme using feature selection,
ICIP10(849-852).
IEEE DOI 1009
BibRef

Torrent, A.[Albert], Lladˇ, X.[Xavier], Freixenet, J.[Jordi], Torralba, A.B.[Antonio B.],
A boosting approach for the simultaneous detection and segmentation of generic objects,
PRL(34), No. 13, 2013, pp. 1490-1498.
Elsevier DOI 1307
BibRef
Earlier:
Simultaneous detection and segmentation for generic objects,
ICIP11(653-656).
IEEE DOI 1201
Object detection. General framework, not just one kind of object. BibRef

Torrent, A.[Albert], Llado, X.[Xavier], Freixenet, J.[Jordi],
Semiautomatic labeling of generic objects for enlarging annotated image databases,
ICIP12(2889-2892).
IEEE DOI 1302
BibRef

Wang, X.Y.[Xiao-Yu], Yang, M.[Ming], Zhu, S.H.[Sheng-Huo], Lin, Y.Q.[Yuan-Qing],
Regionlets for Generic Object Detection,
PAMI(37), No. 10, October 2015, pp. 2071-2084.
IEEE DOI 1509
BibRef
Earlier: ICCV13(17-24)
IEEE DOI 1403
Boosting. DPM BibRef

Liu, L.[Li], Ouyang, W.L.[Wan-Li], Wang, X.G.[Xiao-Gang], Fieguth, P.W.[Paul W.], Chen, J.[Jie], Liu, X.W.[Xin-Wang], Pietikńinen, M.[Matti],
Deep Learning for Generic Object Detection: A Survey,
IJCV(128), No. 2, February 2020, pp. 261-318.
Springer DOI 2002
Survey, Generic Object Detecion. BibRef

Lin, F.[Feng], Hu, W.Z.[Wen-Ze], Wang, Y.W.[Yao-Wei], Tian, Y.H.[Yong-Hong], Lu, G.M.[Guang-Ming], Chen, F.L.[Fang-Lin], Xu, Y.[Yong], Wang, X.Y.[Xiao-Yu],
Universal Object Detection with Large Vision Model,
IJCV(132), No. 4, April 2024, pp. 1258-1276.
Springer DOI 2404
Code:
WWW Link. BibRef

Wu, S.[Shuang], Pei, W.J.[Wen-Jie], Mei, D.[Dianwen], Chen, F.L.[Fang-Lin], Tian, J.D.[Jian-Dong], Lu, G.M.[Guang-Ming],
Multi-faceted Distillation of Base-Novel Commonality for Few-Shot Object Detection,
ECCV22(IX:578-594).
Springer DOI 2211
BibRef

Chen, Y.[Yu], Ma, L.Y.[Li-Yan], Jing, L.P.[Li-Ping], Yu, J.[Jian],
BSDP: Brain-inspired Streaming Dual-level Perturbations for Online Open World Object Detection,
PR(152), 2024, pp. 110472.
Elsevier DOI 2405
Online incremental learning, Open world object detection, Catastrophic forgetting, Prototype-based perturbation BibRef

Zhao, X.W.[Xiao-Wei], Ma, Y.Q.[Yu-Qing], Wang, D.[Duorui], Shen, Y.F.[Yi-Fan], Qiao, Y.X.[Yi-Xuan], Liu, X.L.[Xiang-Long],
Revisiting Open World Object Detection,
CirSysVideo(34), No. 5, May 2024, pp. 3496-3509.
IEEE DOI 2405
Object detection, Task analysis, Benchmark testing, Measurement, Proposals, Training, Labeling, Open world, object detection, class-specific expelling classifier BibRef


Sarkar, H.[Hiran], Chudasama, V.[Vishal], Onoe, N.[Naoyuki], Wasnik, P.[Pankaj], Balasubramanian, V.N.[Vineeth N.],
Open-Set Object Detection By Aligning Known Class Representations,
WACV24(218-227)
IEEE DOI 2404
Measurement, Computational modeling, Semantics, Object detection, Harmonic analysis, Decorrelation, Algorithms BibRef

Wang, Y.H.[Yang-Hao], Yue, Z.Q.[Zhong-Qi], Hua, X.S.[Xian-Sheng], Zhang, H.W.[Han-Wang],
Random Boxes Are Open-world Object Detectors,
ICCV23(6210-6220)
IEEE DOI Code:
WWW Link. 2401
BibRef

Fan, K.[Ke], Bai, Z.C.[Ze-Chen], Xiao, T.J.[Tian-Jun], Zietlow, D.[Dominik], Horn, M.[Max], Zhao, Z.X.[Zi-Xu], Simon-Gabriel, C.J.[Carl-Johann], Shou, M.Z.[Mike Zheng], Locatello, F.[Francesco], Schiele, B.[Bernt], Brox, T.[Thomas], Zhang, Z.[Zheng], Fu, Y.W.[Yan-Wei], He, T.[Tong],
Unsupervised Open-Vocabulary Object Localization in Videos,
ICCV23(13701-13709)
IEEE DOI 2401
BibRef

Pratt, S.[Sarah], Covert, I.[Ian], Liu, R.[Rosanne], Farhadi, A.[Ali],
What does a platypus look like? Generating customized prompts for zero-shot image classification,
ICCV23(15645-15655)
IEEE DOI Code:
WWW Link. 2401
BibRef

Shi, C.[Cheng], Yang, S.[Sibei],
EdaDet: Open-Vocabulary Object Detection Using Early Dense Alignment,
ICCV23(15678-15688)
IEEE DOI 2401
BibRef

Li, W.Y.[Wu-Yang], Guo, X.Q.[Xiao-Qing], Yuan, Y.X.[Yi-Xuan],
Novel Scenes & Classes: Towards Adaptive Open-set Object Detection,
ICCV23(15734-15744)
IEEE DOI Code:
WWW Link. 2401
BibRef

Bao, Z.P.[Zhi-Peng], Tokmakov, P.[Pavel], Wang, Y.X.[Yu-Xiong], Gaidon, A.[Adrien], Hebert, M.[Martial],
Object Discovery from Motion-Guided Tokens,
CVPR23(22972-22981)
IEEE DOI 2309
BibRef

Yang, T.Y.[Tian-Yun], Wang, D.D.[Dan-Ding], Tang, F.[Fan], Zhao, X.Y.[Xin-Ying], Cao, J.[Juan], Tang, S.[Sheng],
Progressive Open Space Expansion for Open-Set Model Attribution,
CVPR23(15856-15865)
IEEE DOI 2309
BibRef

Chen, K.[Keyan], Jiang, X.L.[Xiao-Long], Hu, Y.[Yao], Tang, X.[Xu], Gao, Y.[Yan], Chen, J.Q.[Jian-Qi], Xie, W.[Weidi],
OvarNet: Towards Open-Vocabulary Object Attribute Recognition,
CVPR23(23518-23527)
IEEE DOI 2309
BibRef

Wang, L.T.[Lu-Ting], Liu, Y.[Yi], Du, P.H.[Peng-Hui], Ding, Z.H.[Zi-Han], Liao, Y.[Yue], Qi, Q.S.[Qiao-Song], Chen, B.L.[Biao-Long], Liu, S.[Si],
Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection,
CVPR23(11186-11196)
IEEE DOI 2309
BibRef

Wang, Z.Y.[Zhen-Yu], Li, Y.[Yali], Chen, X.[Xi], Lim, S.N.[Ser-Nam], Torralba, A.[Antonio], Zhao, H.S.[Heng-Shuang], Wang, S.J.[Sheng-Jin],
Detecting Everything in the Open World: Towards Universal Object Detection,
CVPR23(11433-11443)
IEEE DOI 2309
BibRef

Zohar, O.[Orr], Wang, K.C.[Kuan-Chieh], Yeung, S.[Serena],
PROB: Probabilistic Objectness for Open World Object Detection,
CVPR23(11444-11453)
IEEE DOI 2309
BibRef

Xu, M.J.[Ming-Jun], Qin, L.Y.[Ling-Yun], Chen, W.J.[Wei-Jie], Pu, S.L.[Shi-Liang], Zhang, L.[Lei],
Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains,
CVPR23(8103-8112)
IEEE DOI 2309
BibRef

Oin, J.[Jie], Wu, J.[Jie], Yan, P.X.[Peng-Xiang], Li, M.[Ming], Yu-Xi, R.[Ren], Xiao, X.F.[Xue-Feng], Wang, Y.T.[Yi-Tong], Wang, R.[Rui], Wen, S.L.[Shi-Lei], Pan, X.[Xin], Wang, X.G.[Xin-Gang],
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation,
CVPR23(19446-19455)
IEEE DOI 2309
BibRef

Ma, S.L.[Shuai-Lei], Wang, Y.F.[Yue-Feng], Wei, Y.[Ying], Fan, J.Q.[Jia-Qi], Li, T.H.[Thomas H.], Liu, H.L.[Hong-Li], Lv, F.[Fanbing],
CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection,
CVPR23(19681-19690)
IEEE DOI 2309
BibRef

Wu, S.[Size], Zhang, W.W.[Wen-Wei], Jin, S.[Sheng], Liu, W.T.[Wen-Tao], Loy, C.C.[Chen Change],
Aligning Bag of Regions for Open-Vocabulary Object Detection,
CVPR23(15254-15264)
IEEE DOI 2309
BibRef

Zhao, L.[Long], Yuan, L.Z.[Liang-Zhe], Gong, B.Q.[Bo-Qing], Cui, Y.[Yin], Schroff, F.[Florian], Yang, M.H.[Ming-Hsuan], Adam, H.[Hartwig], Liu, T.[Ting],
Unified Visual Relationship Detection with Vision and Language Models,
ICCV23(6939-6950)
IEEE DOI 2401
BibRef

Zhao, S.Y.[Shi-Yu], Zhang, Z.X.[Zhi-Xing], Schulter, S.[Samuel], Zhao, L.[Long], Kumar, B.G.V.[B.G Vijay], Stathopoulos, A.[Anastasis], Chandraker, M.[Manmohan], Metaxas, D.N.[Dimitris N.],
Exploiting Unlabeled Data with Vision and Language Models for Object Detection,
ECCV22(IX:159-175).
Springer DOI 2211

WWW Link. BibRef

Ghiasi, G.[Golnaz], Gu, X.[Xiuye], Cui, Y.[Yin], Lin, T.Y.[Tsung-Yi],
Scaling Open-Vocabulary Image Segmentation with Image-Level Labels,
ECCV22(XXXVI:540-557).
Springer DOI 2211
BibRef

Feng, C.J.[Cheng-Jian], Zhong, Y.J.[Yu-Jie], Jie, Z.[Zequn], Chu, X.X.[Xiang-Xiang], Ren, H.B.[Hai-Bing], Wei, X.L.[Xiao-Lin], Xie, W.[Weidi], Ma, L.[Lin],
PromptDet: Towards Open-Vocabulary Detection Using Uncurated Images,
ECCV22(IX:701-717).
Springer DOI 2211
BibRef

Wu, Z.H.[Zhi-Heng], Lu, Y.[Yue], Chen, X.Y.[Xing-Yu], Wu, Z.X.[Zheng-Xing], Kang, L.W.[Li-Wen], Yu, J.Z.[Jun-Zhi],
UC-OWOD: Unknown-Classified Open World Object Detection,
ECCV22(X:193-210).
Springer DOI 2211
BibRef

Gao, M.F.[Ming-Fei], Xing, C.[Chen], Niebles, J.C.[Juan Carlos], Li, J.[Junnan], Xu, R.[Ran], Liu, W.H.[Wen-Hao], Xiong, C.M.[Cai-Ming],
Open Vocabulary Object Detection with Pseudo Bounding-Box Labels,
ECCV22(X:266-282).
Springer DOI 2211
BibRef

Minderer, M.[Matthias], Gritsenko, A.[Alexey], Stone, A.[Austin], Neumann, M.[Maxim], Weissenborn, D.[Dirk], Dosovitskiy, A.[Alexey], Mahendran, A.[Aravindh], Arnab, A.[Anurag], Dehghani, M.[Mostafa], Shen, Z.[Zhuoran], Wang, X.[Xiao], Zhai, X.H.[Xiao-Hua], Kipf, T.[Thomas], Houlsby, N.[Neil],
Simple Open-Vocabulary Object Detection,
ECCV22(X:728-755).
Springer DOI 2211
BibRef

Lin, Y.T.[Yu-Tong], Li, C.[Chen], Cao, Y.[Yue], Zhang, Z.[Zheng], Wang, J.F.[Jian-Feng], Wang, L.J.[Li-Juan], Liu, Z.C.[Zi-Cheng], Hu, H.[Han],
A Simple Approach and Benchmark for 21,000-Category Object Detection,
ECCV22(XI:1-18).
Springer DOI 2211
BibRef

Zheng, J.Y.[Ji-Yang], Li, W.H.[Wei-Hao], Hong, J.[Jie], Petersson, L.[Lars], Barnes, N.M.[Nick M.],
Towards Open-Set Object Detection and Discovery,
L3D-IVU22(3960-3969)
IEEE DOI 2210
Visualization, Protocols, Object detection, Detectors, Human in the loop BibRef

Han, J.M.[Jia-Ming], Ren, Y.Q.[Yu-Qiang], Ding, J.[Jian], Pan, X.J.[Xing-Jia], Yan, K.[Ke], Xia, G.S.[Gui-Song],
Expanding Low-Density Latent Regions for Open-Set Object Detection,
CVPR22(9581-9590)
IEEE DOI 2210
Measurement, Uncertainty, Codes, Detectors, Object detection, Benchmark testing, Recognition: detection, categorization, retrieval BibRef

Liu, Y.C.[Yen-Cheng], Ma, C.Y.[Chih-Yao], Dai, X.L.[Xiao-Liang], Tian, J.J.[Jun-Jiao], Vajda, P.[Peter], He, Z.J.[Zi-Jian], Kira, Z.[Zsolt],
Open-Set Semi-Supervised Object Detection,
ECCV22(XXX:143-159).
Springer DOI 2211
BibRef

Zareian, A.[Alireza], Rosa, K.D.[Kevin Dela], Hu, D.H.[Derek Hao], Chang, S.F.[Shih-Fu],
Open-Vocabulary Object Detection Using Captions,
CVPR21(14388-14397)
IEEE DOI 2111
Location awareness, Training, Deep learning, Costs, Annotations, Object detection BibRef

Joseph, K.J., Khan, S.[Salman], Khan, F.S.[Fahad Shahbaz], Balasubramanian, V.N.[Vineeth N.],
Towards Open World Object Detection,
CVPR21(5826-5836)
IEEE DOI 2111
Protocols, Computational modeling, Object detection, Detectors, Benchmark testing, Pattern recognition BibRef

Saito, K.[Kuniaki], Hu, P.[Ping], Darrell, T.J.[Trevor J.], Saenko, K.[Kate],
Learning to Detect Every Thing in an Open World,
ECCV22(XXIV:268-284).
Springer DOI 2211
BibRef

Saito, K.[Kuniaki], Ushiku, Y.[Yoshitaka], Harada, T.[Tatsuya], Saenko, K.[Kate],
Strong-Weak Distribution Alignment for Adaptive Object Detection,
CVPR19(6949-6958).
IEEE DOI 2002
BibRef

Lu, S.[Song], Mahadevan, V.[Vijay], Vasconcelos, N.M.[Nuno M.],
Learning Optimal Seeds for Diffusion-Based Salient Object Detection,
CVPR14(2790-2797)
IEEE DOI 1409
diffusion;salient object;seed BibRef

Jiang, P., Vasconcelos, N., Peng, J.,
Generic Promotion of Diffusion-Based Salient Object Detection,
ICCV15(217-225)
IEEE DOI 1602
Algorithm design and analysis BibRef

Novotny, D.[David], Matas, J.G.[Jiri G.],
Cascaded Sparse Spatial Bins for Efficient and Effective Generic Object Detection,
ICCV15(1152-1160)
IEEE DOI 1602
Detectors based on HoG. BibRef

Zou, W.[Will], Wang, X.Y.[Xiao-Yu], Sun, M.[Miao], Lin, Y.Q.[Yuan-Qing],
Generic Object Detection with Dense Neural Patterns and Regionlets,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Siva, P.[Parthipan], Russell, C.[Chris], Xiang, T.[Tao], Agapito, L.[Lourdes],
Looking Beyond the Image: Unsupervised Learning for Object Saliency and Detection,
CVPR13(3238-3245)
IEEE DOI 1309
Generic Object Detection; Object Saliency; Weakly Supervised Learning BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Dense Object Detection .


Last update:May 23, 2024 at 14:31:23