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20242026
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cs.CV2026

Audio-Visual Segmentation via Depth-Guided Collaborative Modeling

Zhaojin Fu, Yuyang Hong, Qi Yang +4

Audio-Visual Segmentation (AVS) is a fundamental task in multimodal perception that performs pixel-level segmentation of sounding objects in videos by leveraging both visual and au…

cs.CV2026

Continuous Speculative Decoding for Autoregressive Image Generation

Zili Wang, Zheng Zhang, Kun Ding +3

Continuous visual autoregressive (AR) models have demonstrated promising performance in image generation, but their inherently sequential nature results in slow inference speed. Sp…

cs.CV2026

Beyond Sequential Distance: Inter-Modal Distance Invariant Position Encoding

Lin Chen, Bolin Ni, Qi Yang +5

Despite the remarkable capabilities of Multimodal Large Language Models (MLLMs), they still suffer from visual fading in long-context scenarios. Specifically, the attention to visu…

cs.CV2026

WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering

Yingjian Zhu, Xinming Wang, Kun Ding +3

Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-VQA). Despite recent advancements, pre…

cs.CV2026

SeaVIS: Sound-Enhanced Association for Online Audio-Visual Instance Segmentation

Yingjian Zhu, Ying Wang, Yuyang Hong +5

Recently, an audio-visual instance segmentation (AVIS) task has been introduced, aiming to identify, segment and track individual sounding instances in videos. However, prevailing…

cs.CV2026

CC-VQA: Conflict- and Correlation-Aware Method for Mitigating Knowledge Conflict in Knowledge-Based Visual Question Answering

Yuyang Hong, Jiaqi Gu, Yujin Lou +7

Knowledge-based visual question answering (KB-VQA) demonstrates significant potential for handling knowledge-intensive tasks. However, conflicts arise between static parametric kno…