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AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection
21 September 2017
Thanh-Toan Do
A. Nguyen
Ian Reid
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Papers citing
"AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection"
50 / 172 papers shown
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3D Affordance Keypoint Detection for Robotic Manipulation
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116
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Closed-Loop Transfer for Weakly-supervised Affordance Grounding
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149
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20 Oct 2025
H2OFlow: Grounding Human-Object Affordances with 3D Generative Models and Dense Diffused Flows
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129
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76
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101
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02 Oct 2025
AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation
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109
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01 Oct 2025
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136
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144
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Weakly-Supervised Learning of Dense Functional Correspondences
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125
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Object Affordance Recognition and Grounding via Multi-scale Cross-modal Representation Learning
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121
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Yanping Fu
Saike Huang
Yingfei Liu
Fan Jia
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Feng Dai
Tiancai Wang
Rao Muhammad Anwer
Fahad Shahbaz Khan
Jianbing Shen
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113
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Jie Feng
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Weiming Dong
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Yuhui Zheng
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G. Shi
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153
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301
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Shiyi Wang
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317
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UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation
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Yihe Tang
Wenlong Huang
Yingke Wang
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315
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292
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Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors
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474
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Rose Hendrix
428
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493
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386
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Korbinian Franz Rudolf
Nils Blank
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237
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250
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Quyu Kong
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214
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116
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377
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461
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187
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252
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302
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