University of Oxford · embodied AI & robot learning牛津大学 · 具身智能与机器人学习
3 curated papers, code, datasets and hardware from University of Oxford (3 with code), with one-line takeaways.3 个来自牛津大学的精选论文、代码、数据集与硬件（3 个附代码），均配一句话要点。
Labs are matched from each entry's affiliation field by simple name rules (data/labs.yaml); joint work appears under every lab named. Only curated entries are listed, because daily arXiv papers carry no affiliations.机构由每个条目的机构字段按名称规则匹配（data/labs.yaml），合作工作会出现在所有署名机构下。仅列出精选条目，因为每日 arXiv 论文不含机构信息。
One feed-forward transformer predicts cameras, depth, point maps and tracks for many views at once, in about a second.单个前馈 Transformer 一次性为多视角图像预测相机参数、深度、点图与跟踪，约一秒完成。
@misc{wang2025vggt,
title = {{VGGT: Visual Geometry Grounded Transformer}},
author = {Jianyuan Wang and Minghao Chen and Nikita Karaev and Andrea Vedaldi and Christian Rupprecht and David Novotny},
year = {2025},
eprint = {2503.11651},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2503.11651},
}
Transformer that tracks many video points jointly rather than one at a time, staying robust through occlusions; widely used to extract motion tracks from human or robot videos for policy learning.联合跟踪视频中大量点（而非逐点独立跟踪）的 Transformer，遮挡下依然稳健；常用于从人类或机器人视频中提取运动轨迹来学习策略。
@misc{karaev2023cotracker,
title = {{CoTracker: It is Better to Track Together}},
author = {Nikita Karaev and Ignacio Rocco and Benjamin Graham and Natalia Neverova and Andrea Vedaldi and Christian Rupprecht},
year = {2023},
eprint = {2307.07635},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2307.07635},
}
A fast, robust ADMM-based QP solver with warm starting and embedded C code generation; widely used inside MPC and whole-body controllers.基于 ADMM 的快速、鲁棒二次规划求解器，支持热启动与嵌入式 C 代码生成，广泛用于 MPC 与全身控制器。
@misc{stellato2017osqp,
title = {{OSQP: An Operator Splitting Solver for Quadratic Programs}},
author = {Bartolomeo Stellato and Goran Banjac and Paul Goulart and Alberto Bemporad and Stephen Boyd},
year = {2017},
eprint = {1711.08013},
archivePrefix = {arXiv},
primaryClass = {math.OC},
url = {https://arxiv.org/abs/1711.08013},
}