5 papers
ContextFlow: In-Context Flow Matching for Robot Manipulation
Jian Ding, Xianjie Dai, Roei Herzig +5
Although highly effective in vision and language domains, applying in-context learning to robotics remains challenging. Existing autoregressive in-context imitation methods discret…
Artic-O: End-to-End Articulated Object Reconstruction via Latent Geometry Learning
Xuyang Wang, Zhenyu Li, Jian Ding +4
Reconstructing articulated objects from sparse images requires recovering complete geometry, movable parts, and motion parameters. Recent methods typically separate geometry recons…
Afford-VLA: Action-Aligned Visual Planning via Internalized Affordance
Runze Wang, Yuqian Fu, Yu Li +7
Vision-language-action (VLA) models have shown strong potential for generalist robot manipulation, yet they remain limited by insufficient spatial reasoning, particularly in determ…
The Second Challenge on Cross-Domain Few-Shot Object Detection at NTIRE 2026: Methods and Results
Xingyu Qiu, Yuqian Fu, Jiawei Geng +70
Cross-domain few-shot object detection (CD-FSOD) remains a challenging problem for existing object detectors and few-shot learning approaches, particularly when generalizing across…
Video Object Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting
Mennatullah Siam, Chen Jiang, Steven Lu +4
Video object segmentation is an essential task in robot manipulation to facilitate grasping and learning affordances. Incremental learning is important for robotics in unstructured…