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cs.CV2026
Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs
Qi Li, Yanzhe Zhao, Yongxin Zhou +4
Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various modalities for a given query. Ho…
cs.CV2024
DENOISER: Rethinking the Robustness for Open-Vocabulary Action Recognition
Haozhe Cheng, Cheng Ju, Haicheng Wang +5
As one of the fundamental video tasks in computer vision, Open-Vocabulary Action Recognition (OVAR) recently gains increasing attention, with the development of vision-language pre…
cs.CV2024
Audio-Visual Segmentation via Unlabeled Frame Exploitation
Jinxiang Liu, Yikun Liu, Fei Zhang +3
Audio-visual segmentation (AVS) aims to segment the sounding objects in video frames. Although great progress has been witnessed, we experimentally reveal that current methods reac…