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20242026
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cs.CV2026

GA2-CLIP: Generic Attribute Anchor for Efficient Prompt Tuningin Video-Language Models

Bin Wang, Ruotong Hu, Wentong Li +5

Visual and textual soft prompt tuning can effectively improve the adaptability of Vision-Language Models (VLMs) in downstream tasks. However, fine-tuning on video tasks impairs the…

cs.CV2025

Divide-and-Conquer Decoupled Network for Cross-Domain Few-Shot Segmentation

Runmin Cong, Anpeng Wang, Bin Wan +3

Cross-domain few-shot segmentation (CD-FSS) aims to tackle the dual challenge of recognizing novel classes and adapting to unseen domains with limited annotations. However, encoder…

cs.CV2025

The 1st Solution for 4th PVUW MeViS Challenge: Unleashing the Potential of Large Multimodal Models for Referring Video Segmentation

Hao Fang, Runmin Cong, Xiankai Lu +2

Motion expression video segmentation is designed to segment objects in accordance with the input motion expressions. In contrast to the conventional Referring Video Object Segmenta…

cs.CV2024

Query-guided Prototype Evolution Network for Few-Shot Segmentation

Runmin Cong, Hang Xiong, Jinpeng Chen +3

Previous Few-Shot Segmentation (FSS) approaches exclusively utilize support features for prototype generation, neglecting the specific requirements of the query. To address this, w…

cs.CV2024

SDDNet: Style-guided Dual-layer Disentanglement Network for Shadow Detection

Runmin Cong, Yuchen Guan, Jinpeng Chen +3

Despite significant progress in shadow detection, current methods still struggle with the adverse impact of background color, which may lead to errors when shadows are present on c…

cs.CV2024

Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection

Runmin Cong, Hongyu Liu, Chen Zhang +4

By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved. In recent y…