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6-DoF grasp detection has been a fundamental and challenging problem in robotic vision.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Efficient grasping from rgbd images: Learning using a new rectangle representation
Yun Jiang, Stephen Moseson, and Ashutosh Saxena · 2011
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Lie groups and algebraic groups
Arkadij L Onishchik and Ernest B Vinberg · 2012
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Notes on Lie algebras
Hans Samelson · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Deep learning for detecting robotic grasps
Ian Lenz, Honglak Lee, and Ashutosh Saxena · 2015
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Real-time grasp detection using convolutional neural networks
Joseph Redmon and Anelia Angelova · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Review of deep learning methods in robotic grasp detection
Shehan Caldera, Alexander Rassau, and Douglas Chai · 2018
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Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach
Douglas Morrison, Peter Corke, and Jürgen Leitner · 2018
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On the Covariance
Huy Nguyen and Quang-Cuong Pham · 2018
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Robotiq 2f-140
Robotiq · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Implicit generation and modeling with energy based models
Yilun Du and Igor Mordatch · 2019
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Pointnetgpd: Detecting grasp configurations from point sets
Hongzhuo Liang, Xiaojian Ma, Shuang Li, Michael Görner, Song Tang, Bin Fang, Fuchun Sun, and Jianwei Zhang · 2019
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6-dof graspnet: Variational grasp generation for object manipulation
Arsalan Mousavian, Clemens Eppner, and Dieter Fox · 2019
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Roi-based robotic grasp detection for object overlapping scenes
Hanbo Zhang, Xuguang Lan, Site Bai, Xinwen Zhou, Zhiqiang Tian, and Nanning Zheng · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Compositional visual generation with energy based models
Yilun Du, Shuang Li, and Igor Mordatch · 2020
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Graspnet-1billion: A large-scale benchmark for general object grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou, and Cewu Lu · 2020
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Learning the stein discrepancy for training and evaluating energy-based models without sampling
Will Grathwohl, Kuan-Chieh Wang, Jörn-Henrik Jacobsen, David Duvenaud, and Richard Zemel · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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A survey on learning-based robotic grasping
Kilian Kleeberger, Richard Bormann, Werner Kraus, and Marco F Huber · 2020
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Antipodal robotic grasping using generative residual convolutional neural network
Sulabh Kumra, Shirin Joshi, and Ferat Sahin · 2020
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6-dof grasping for target-driven object manipulation in clutter
Adithyavairavan Murali, Arsalan Mousavian, Clemens Eppner, Chris Paxton, and Dieter Fox · 2020
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Pointnet++ grasping: Learning an end-to-end spatial grasp generation algorithm from sparse point clouds
Peiyuan Ni, Wenguang Zhang, Xiaoxiao Zhu, and Qixin Cao · 2020
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On the anatomy of mcmc-based maximum likelihood learning of energy-based models
Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, and Ying Nian Wu · 2020
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S4g: Amodal single-view single-shot se (3) grasp detection in cluttered scenes
Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, and Hao Su · 2020
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End-to-end trainable deep neural network for robotic grasp detection and semantic segmentation from rgb
Stefan Ainetter and Friedrich Fraundorfer · 2021
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Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne Van Den Berg · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Improved contrastive divergence training of energy-based models
Yilun Du, Shuang Li, Joshua Tenenbaum, and Igor Mordatch · 2021
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Acronym: A large-scale grasp dataset based on simulation
Clemens Eppner, Arsalan Mousavian, and Dieter Fox · 2021
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Rgb matters: Learning 7-dof grasp poses on monocular rgbd images
Minghao Gou, Hao-Shu Fang, Zhanda Zhu, Sheng Xu, Chenxi Wang, and Cewu Lu · 2021
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Align before fuse: Vision and language representation learning with momentum distillation
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, and Steven Chu Hong Hoi · 2021
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Diffusion probabilistic models for 3d point cloud generation
Shitong Luo and Wei Hu · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Difffacto: Controllable part-based 3d point cloud generation with cross diffusion
George Kiyohiro Nakayama, Mikaela Angelina Uy, Jiahui Huang, Shi-Min Hu, Ke Li, and Leonidas Guibas · 2023
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Open-vocabulary affordance detection in 3d point clouds
Toan Nguyen, Minh Nhat Vu, An Vuong, Dzung Nguyen, Thieu Vo, Ngan Le, and Anh Nguyen · 2023
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GPT-4 technical report
OpenAI · 2023
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Language embedded radiance fields for zero-shot task-oriented grasping
Adam Rashid, Satvik Sharma, Chung Min Kim, Justin Kerr, Lawrence Yunliang Chen, Angjoo Kanazawa, and Ken Goldberg · 2023
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Leveraging language for accelerated learning of tool manipulation
Allen Z Ren, Bharat Govil, Tsung-Yen Yang, Karthik R Narasimhan, and Anirudha Majumdar · 2023
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Consistency models
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Maximum likelihood training of score-based diffusion models
Yang Song, Conor Durkan, Iain Murray, and Stefano Ermon · 2021
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Contact-graspnet: Efficient 6-dof grasp generation in cluttered scenes
Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, and Dieter Fox · 2021
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Graspness discovery in clutters for fast and accurate grasp detection
Chenxi Wang, Hao-Shu Fang, Minghao Gou, Hongjie Fang, Jin Gao, and Cewu Lu · 2021
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Regnet: Region-based grasp network for end-to-end grasp detection in point clouds
Binglei Zhao, Hanbo Zhang, Xuguang Lan, Haoyu Wang, Zhiqiang Tian, and Nanning Zheng · 2021
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Graspgpt: Leveraging semantic knowledge from a large language model for task-oriented grasping
Chao Tang, Dehao Huang, Wenqi Ge, Weiyu Liu, and Hong Zhang · 2023
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Task-oriented grasp prediction with visual-language inputs
Chao Tang, Dehao Huang, Lingxiao Meng, Weiyu Liu, and Hong Zhang · 2023
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Language-guided robot grasping: Clip-based referring grasp synthesis in clutter
Georgios Tziafas, XU Yucheng, Arushi Goel, Mohammadreza Kasaei, Zhibin Li, and Hamidreza Kasaei · 2023
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Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Jan Peters, and Georgia Chalvatzaki · 2023
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Machine learning-based framework for optimally solving the analytical inverse kinematics for redundant manipulators
Minh Nhat Vu, Florian Beck, Michael Schwegel, Christian Hartl-Nesic, Anh Nguyen, and Andreas Kugi · 2023
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Fg-t2m: Fine-grained text-driven human motion generation via diffusion model
Yin Wang, Zhiying Leng, Frederick WB Li, Shun-Cheng Wu, and Xiaohui Liang · 2023
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Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation
Jay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei, Yuchao Gu, Yufei Shi, Wynne Hsu, Ying Shan, Xiaohu Qie, and Mike Zheng Shou · 2023
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Unifying diffusion models with action detection transformers for multi-task robotic manipulation
Zhou Xian, Nikolaos Gkanatsios, Theophile Gervet, and Katerina Fragkiadaki · 2023
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Smartbrush: Text and shape guided object inpainting with diffusion model
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, and Kun Zhang · 2023
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A joint modeling of vision-language-action for target-oriented grasping in clutter
Kechun Xu, Shuqi Zhao, Zhongxiang Zhou, Zizhang Li, Huaijin Pi, Yifeng Zhu, Yue Wang, and Rong Xiong · 2023
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Xskill: Cross embodiment skill discovery
Mengda Xu, Zhenjia Xu, Cheng Chi, Manuela Veloso, and Shuran Song · 2023
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Gnfactor: Multi-task real robot learning with generalizable neural feature fields
Yanjie Ze, Ge Yan, Yueh-Hua Wu, Annabella Macaluso, Yuying Ge, Jianglong Ye, Nicklas Hansen, Li Erran Li, and Xiaolong Wang · 2023
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Rt-2: Vision-language-action models transfer web knowledge to robotic control
Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, et al · 2023
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Compositional foundation models for hierarchical planning
Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi Jaakkola, Josh Tenenbaum, Leslie Kaelbling, Akash Srivastava, and Pulkit Agrawal · 2024
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Learning universal policies via text-guided video generation
Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, and Pieter Abbeel · 2024
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Learning to act from actionless videos through dense correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du, Shao-Hua Sun, and Joshua B. Tenenbaum · 2024
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Posediff: Pose-conditioned multimodal diffusion model for unbounded scene synthesis from sparse inputs
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Language-conditioned affordance-pose detection in 3d point clouds
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Video generation models as world simulators
OpenAI · 2024
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Open-vocabulary affordance detection using knowledge distillation and text-point correlation
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Language-driven grasp detection
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Grasp-anything: Large-scale grasp dataset from foundation models
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Language-driven scene synthesis using multi-conditional diffusion model
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Diffusebot: Breeding soft robots with physics-augmented generative diffusion models
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