6 papers
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…
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…
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…
Open-Vocabulary Animal Keypoint Detection with Semantic-feature Matching
Hao Zhang, Lumin Xu, Shenqi Lai +5
Current image-based keypoint detection methods for animal (including human) bodies and faces are generally divided into full-supervised and few-shot class-agnostic approaches. The…