43 citations · 89 across the 14 of their papers we have counts for
5 papers · 1 filter
Ultra-High Resolution Segmentation via Boundary-Enhanced Patch-Merging Transformer
Haopeng Sun, Yingwei Zhang, Lumin Xu +2
Segmentation of ultra-high resolution (UHR) images is a critical task with numerous applications, yet it poses significant challenges due to high spatial resolution and rich fine d…
KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension
Jie Yang, Wang Zeng, Sheng Jin +4
Recent advancements in Multimodal Large Language Models (MLLMs) have greatly improved their abilities in image understanding. However, these models often struggle with grasping pix…
TCFormer: Visual Recognition via Token Clustering Transformer
Wang Zeng, Sheng Jin, Lumin Xu +5
Transformers are widely used in computer vision areas and have achieved remarkable success. Most state-of-the-art approaches split images into regular grids and represent each grid…
F-LMM: Grounding Frozen Large Multimodal Models
Size Wu, Sheng Jin, Wenwei Zhang +4
Endowing Large Multimodal Models (LMMs) with visual grounding capability can significantly enhance AIs' understanding of the visual world and their interaction with humans. However…
UniFS: Universal Few-shot Instance Perception with Point Representations
Sheng Jin, Ruijie Yao, Lumin Xu +4
Instance perception tasks (object detection, instance segmentation, pose estimation, counting) play a key role in industrial applications of visual models. As supervised learning m…