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New TV-AudioRemover framework enables multimodal sound removal from videos

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced TV-AudioRemover, a novel framework designed to remove sounds associated with specific visual objects from videos. Unlike previous methods that relied on single-modal control, TV-AudioRemover utilizes both the visually edited video and natural-language instructions for more effective multimodal guidance. The project also includes the creation of a large-scale dataset for training, a comprehensive benchmark called AV-Remove-Bench for evaluation, and an MLLM-based assessment protocol. AI

IMPACT This research could lead to more sophisticated video editing tools by enabling precise audio manipulation synchronized with visual edits.

RANK_REASON This is a research paper describing a new method and dataset. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New TV-AudioRemover framework enables multimodal sound removal from videos

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This is a research paper describing a new method and dataset. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xinyue Guo, Jianxuan Yang, Daiguo Zhou, Jiagao Hu, Yuxuan Chen, Fei Wang, Jian Luan ·

    TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculum

    arXiv:2609.25864v2 Announce Type: replace-cross Abstract: Visual object removal can eliminate a target from video frames, yet its acoustic trace persists in the soundtrack, causing obvious audio-visual inconsistency. Existing video inpainting models operate solely on pixels, whil…

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