activity
20242026
most citedSemi-LLIE: Semi-supervised Contrastive Learning with Mamba-based Low-light Image Enhancement

2 citations · 2 across the 5 of their papers we have counts for

collaborators

12 papers

cs.CV2026

Understanding Degradation with Vision Language Model

Guanzhou Lan, Chenyi Liao, Yuqi Yang +5

Understanding visual degradations is a critical yet challenging problem in computer vision. While recent Vision-Language Models (VLMs) excel at qualitative description, they often…

cs.RO2025

FastUMI-100K: Advancing Data-driven Robotic Manipulation with a Large-scale UMI-style Dataset

Kehui Liu, Zhongjie Jia, Yang Li +14

Data-driven robotic manipulation learning depends on large-scale, high-quality expert demonstration datasets. However, existing datasets, which primarily rely on human teleoperated…

cs.RO2025

MLM: Learning Multi-task Loco-Manipulation Whole-Body Control for Quadruped Robot with Arm

Xin Liu, Bida Ma, Chenkun Qi +14

Whole-body loco-manipulation for quadruped robots with arms remains a challenging problem, particularly in achieving multi-task control. To address this, we propose MLM, a reinforc…

cs.CV2025

Cross from Left to Right Brain: Adaptive Text Dreamer for Vision-and-Language Navigation

Pingrui Zhang, Yifei Su, Pengyuan Wu +7

Vision-and-Language Navigation (VLN) requires the agent to navigate by following natural instructions under partial observability, making it difficult to align perception with lang…

cs.RO2025

Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation

Yuanqi Yao, Siao Liu, Haoming Song +7

Building a lifelong robot that can effectively leverage prior knowledge for continuous skill acquisition remains significantly challenging. Despite the success of experience replay…

cs.RO2025

Hume: Introducing System-2 Thinking in Visual-Language-Action Model

Haoming Song, Delin Qu, Yuanqi Yao +9

Humans practice slow thinking before performing actual actions when handling complex tasks in the physical world. This thinking paradigm, recently, has achieved remarkable advancem…