📡 Embodied AI Radar具身智能雷达 Star2

Most of this project is curated by Claude. Drop a star to cheer Claude on!本项目大量由 Claude 整理维护,点个 Star 给克劳德大小姐鼓励一下!

★ Feed a star投喂 Star

Venues会议/期刊 › ICCV 2025

ICCV 2025 · papers论文

3 embodied-AI and robotics papers accepted at ICCV 2025, 3 with code.3 篇被 ICCV 2025 接收的具身智能与机器人论文,其中 3 篇附代码。

arXiv 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. For CoRL 2026 the official program is used as well.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。CoRL 2026 另依据官方日程。

Search within this venue series →在该会议/期刊系列中搜索 →

Curated精选 (3)

Paper论文 2025 ICCV 2025 new新 2026-11-04

GWM: Towards Scalable Gaussian World Models for Robotic Manipulation

Predicts future states by propagating Gaussian primitives under robot actions with a latent DiT and 3D VAE, usable for representation learning and as a neural simulator.用潜空间 DiT 和 3D VAE 预测高斯基元在机器人动作下的传播,可用于表征学习,也可作为神经模拟器。

BibTeX
@misc{lu2025gwm,
  title = {{GWM: Towards Scalable Gaussian World Models for Robotic Manipulation}},
  author = {Guanxing Lu and Baoxiong Jia and Puhao Li and Yixin Chen and Ziwei Wang and Yansong Tang and Siyuan Huang},
  year = {2025},
  eprint = {2508.17600},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2508.17600},
}
World Models世界模型gaussian-splatting3d
Paper论文 2024 ICCV 2025

UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI

Over 100 photorealistic Unreal Engine worlds with playable humans, animals, robots and vehicles for embodied AI research.100 多个基于虚幻引擎的高真实感世界,含可操控的人、动物、机器人和车辆,服务具身智能研究。

BibTeX
@misc{zhong2024unrealzoo,
  title = {{UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI}},
  author = {Fangwei Zhong and Kui Wu and Churan Wang and Hao Chen and Hai Ci and Zhoujun Li and Yizhou Wang},
  year = {2024},
  eprint = {2412.20977},
  archivePrefix = {arXiv},
  primaryClass = {cs.AI},
  url = {https://arxiv.org/abs/2412.20977},
}
Sim-to-Real & Simulators仿真与 Sim-to-Realsimulatorunreal-enginephotorealistic
Paper论文 2025 · Shanghai AI Lab / SJTU ICCV 2025

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Replaces OpenVLA's per-dimension action bins with a convolutional residual VQ-VAE tokenizer trained on 100x more (real + synthetic) data; reports higher LIBERO-90 and real Franka success and ~2.8x faster inference.用卷积残差 VQ-VAE 动作分词器(以百倍规模的真实+合成数据训练)替换 OpenVLA 的逐维离散分箱;论文报告 LIBERO-90 和真实 Franka 任务成功率提升,推理速度约快 2.8 倍。

BibTeX
@misc{wang2025vq,
  title = {{VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers}},
  author = {Yating Wang and Haoyi Zhu and Mingyu Liu and Jiange Yang and Hao-Shu Fang and Tong He},
  year = {2025},
  eprint = {2507.01016},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2507.01016},
}
VLA & Robot Foundation ModelsVLA 与机器人基础模型Robot arm机械臂realsimarmaction-tokenizer