4 citations · 7 across the 2 of their papers we have counts for
6 papers · 1 filter
KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model
Jie Yang, Wang Zeng, Sheng Jin +5
The emergence of Multimodal Large Language Models (MLLMs) has revolutionized image understanding by bridging textual and visual modalities. However, these models often struggle wit…
Harmonizing Visual Representations for Unified Multimodal Understanding and Generation
Size Wu, Wenwei Zhang, Lumin Xu +6
Unifying visual understanding and generation within a single multimodal framework remains a significant challenge, as the two inherently heterogeneous tasks require representations…
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…
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search
Lumin Xu, Yingda Guan, Sheng Jin +5
Human pose estimation has achieved significant progress in recent years. However, most of the recent methods focus on improving accuracy using complicated models and ignoring real-…
Whole-Body Human Pose Estimation in the Wild
Sheng Jin, Lumin Xu, Jin Xu +5
This paper investigates the task of 2D human whole-body pose estimation, which aims to localize dense landmarks on the entire human body including face, hands, body, and feet. As e…