8 papers
Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation
Jiahao Nie, Guanqiao Fu, Wenbin An +3
Cross-Domain Few-Shot Segmentation aims to segment categories in data-scarce domains conditioned on a few exemplars. Typical methods first establish few-shot capability in a large-…
Referring Multiple Regions with Large Multimodal Models via Contextual Latent Steering
Yun Xing, Hanyuan Liu, Jiahao Nie +1
Large Multimodal Models (LMMs) have recently demonstrated their proficiency in holistic visual comprehension. However, most of them struggle to tackle region-level perception guide…
Boosting SAM for Cross-Domain Few-Shot Segmentation via Conditional Point Sparsification
Jiahao Nie, Yun Xing, Wenbin An +6
Motivated by the success of the Segment Anything Model (SAM) in promptable segmentation, recent studies leverage SAM to develop training-free solutions for few-shot segmentation, w…
E.M.Ground: A Temporal Grounding Vid-LLM with Holistic Event Perception and Matching
Jiahao Nie, Wenbin An, Gongjie Zhang +4
Despite recent advances in Video Large Language Models (Vid-LLMs), Temporal Video Grounding (TVG), which aims to precisely localize time segments corresponding to query events, rem…
MMRel: Benchmarking Relation Understanding in Multi-Modal Large Language Models
Jiahao Nie, Gongjie Zhang, Wenbin An +4
Though Multi-modal Large Language Models (MLLMs) have recently achieved significant progress, they often struggle to understand diverse and complicated inter-object relations. Spec…
Empowering Multimodal LLMs with External Tools: A Comprehensive Survey
Wenbin An, Jiahao Nie, Yaqiang Wu +3
By integrating the perception capabilities of multimodal encoders with the generative power of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), exemplified b…