5 embodied-AI and robotics papers accepted at CVPR 2023, 3 with code.5 篇被 CVPR 2023 接收的具身智能与机器人论文，其中 3 篇附代码。
Feed papers are listed when their arXiv comment says they were accepted (e.g. 'Accepted to CoRL 2026'); papers that do not say so are missing, and the list grows as authors post camera-ready versions. Curated entries carry a hand-checked venue.日常 arXiv 论文仅在其 arXiv 备注写明已被接收（如 “Accepted to CoRL 2026”）时列入；未注明的论文不会出现，列表会随作者上传终稿而增加。精选条目的会议/期刊信息经过人工核对。
2.1M video frames of two hands manipulating articulated objects (scissors, laptops…) with accurate 3D hand and object meshes from motion capture; a reference for bimanual hand-object reconstruction.210 万帧双手操作铰接物体（剪刀、笔记本电脑等）的视频，借助动作捕捉提供精确的手与物体三维网格；双手-物体重建的常用基准。
@misc{fan2022arctic,
title = {{ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation}},
author = {Zicong Fan and Omid Taheri and Dimitrios Tzionas and Muhammed Kocabas and Manuel Kaufmann and Michael J. Black and Otmar Hilliges},
year = {2022},
eprint = {2204.13662},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2204.13662},
}
Tracks the 6-DoF pose of a never-seen object in RGB-D video while building its neural 3D model online, with no CAD model needed; useful for manipulating novel objects.在 RGB-D 视频中跟踪从未见过物体的六自由度位姿，同时在线构建其神经三维模型，无需 CAD 模型；适用于操作新物体。
@misc{wen2023bundlesdf,
title = {{BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects}},
author = {Bowen Wen and Jonathan Tremblay and Valts Blukis and Stephen Tyree and Thomas Muller and Alex Evans and Dieter Fox and Jan Kautz and Stan Birchfield},
year = {2023},
eprint = {2303.14158},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2303.14158},
}
CLIP on Wheels pairs open-vocabulary localization (CLIP-style models, no fine-tuning) with classical exploration for zero-shot object navigation; the Pasture benchmark adds rare, attribute-described and hidden objects.CoWs on Pasture：CLIP on Wheels 把开放词汇定位（CLIP 等模型，无需微调）与经典探索结合，实现零样本目标物体导航；配套的 Pasture 基准加入了少见物体、按属性描述的物体和被遮挡物体。
@misc{gadre2022cows,
title = {{CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation}},
author = {Samir Yitzhak Gadre and Mitchell Wortsman and Gabriel Ilharco and Ludwig Schmidt and Shuran Song},
year = {2022},
eprint = {2203.10421},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2203.10421},
}
800K+ annotated 3D object models; widely used to populate simulators with diverse objects for grasping, rearrangement and procedural scene generation (Objaverse-XL extends it to 10M+).80 万+ 带标注的 3D 物体模型，常用于为仿真器填充多样物体，用于抓取、重排和程序化场景生成（Objaverse-XL 扩展到 1000 万+）。
@misc{deitke2022objaverse,
title = {{Objaverse: A Universe of Annotated 3D Objects}},
author = {Matt Deitke and Dustin Schwenk and Jordi Salvador and Luca Weihs and Oscar Michel and Eli VanderBilt and Ludwig Schmidt and Kiana Ehsani and Aniruddha Kembhavi and Ali Farhadi},
year = {2022},
eprint = {2212.08051},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2212.08051},
}
PIRLNav — behavior cloning on human ObjectNav demonstrations, then RL fine-tuning of the same policy; the paper reports 65.0% success on Habitat ObjectNav, 5 points above the previous best.PIRLNav：先在人类 ObjectNav 演示上做行为克隆，再用强化学习微调同一策略；论文报告在 Habitat ObjectNav 上成功率 65.0%，比此前最佳高 5 个百分点。
@misc{ramrakhya2023pirlnav,
title = {{PIRLNav: Pretraining with Imitation and RL Finetuning for ObjectNav}},
author = {Ram Ramrakhya and Dhruv Batra and Erik Wijmans and Abhishek Das},
year = {2023},
eprint = {2301.07302},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2301.07302},
}