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Matching papers

Self-Supervised Learning of Structured Dynamics from Videos

13 upvotes · 23 JUL 2026 · Lukas Knobel, Andrew Zisserman, Yuki M. Asano

This paper learns how to separate the motion in videos into two parts: the camera's movement and the objects' movements, allowing for more accurate and meaningful analysis of the video content. Practitioners might care because this can improve the performance of computer vision models on tasks like object tracking and motion analysis.

video representation learningstructured dynamicsself-supervised learningvision transformersmotion analysis

SVR-R1: Bootstrapping Multi-modal Reasoning with Self-verification in Reinforcement Learning

3 upvotes · 13 JUL 2026 · Mingyuan Wu, Jingcheng Yang, Shengyi Qian et al.

This paper introduces a new reinforcement learning framework called SVR-R1 that helps models improve their reasoning abilities by giving them the chance to correct their own mistakes. Practitioners might care about this because it could lead to better performance in tasks that require complex reasoning.

reinforcement learningmultimodal reasoningself-supervised learningvision-language modelsbootstrapping