Hugging Face Trending Papers
From Visual Cues to Spoken Narration: Rethinking Audio Description
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arXiv Computer Vision
Sep 3
From Visual Cues to Spoken Narration: Rethinking Audio Description
The paper introduces Cue2Narrate, a two‑stage pipeline that jointly predicts what visual events to narrate and when to insert the narration in long, untrimmed movie clips. It uses a dual‑head audio‑visual localizer to identify visual cue and narration windows, followed by a LoRA‑adapted vision‑language model that generates concise audio descriptions, trained with a Description Ranking Loss. The authors also present the LongLSMDC benchmark, comprising up to 8‑minute clips, and show that Cue2Narrate outperforms video‑only and audio‑only baselines by 5–12 points in average mAP and improves AD generation over fine‑tuned base VLMs.
arXiv AI
Aug 25
Pre-Decoding Acoustic Triage for Budgeted Vision-Language Captioning of Untrimmed Egocentric Video
The paper introduces an audio-first triage method for budgeted vision‑language captioning of untrimmed egocentric video. By selecting windows for a vision‑language model based on lightweight audio features before any video decoding, the approach reduces costly model calls. It achieves 4.0–10.8 percentage point improvements in action coverage across call rates, cuts 9–20% of VLM calls at matched coverage on EPIC‑KITCHENS‑100, and outperforms uniform sampling and recent visual keyframe selectors on Ego4D.
arXiv AI
Jul 14
StoryTeller: Training-Free Narrative Grounding for Long-Form Audio Description
arXiv:2607. 11798v1 Announce Type: cross Abstract: Long-form audio description (AD) requires more than describing visible actions: it must preserve characters, events, relationships, and story context across scenes so that blind and low-vision (BLV) audiences can follow a film.
arXiv Computer Vision
3d ago
Candor-LR: A Dyadic Conversational Dataset for Audio-Visual Speech Recognition
arXiv:2609.10394v1 Announce Type: cross Abstract: Current audio-visual speech recognition (AVSR) benchmarks, like LRS3, rely heavily on clean, scripted and rehearsed speech. They fail to reflect the...
arXiv Computation and Language
3d ago
Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs
arXiv:2609.10355v1 Announce Type: cross Abstract: Video understanding has rapidly evolved toward video large language models (VideoLLMs): systems that couple video representations with pretrained lar...
arXiv Machine Learning
Jul 14
Empowering Long-form Omni-modal Understanding with Robust Audio Perception
arXiv:2607. 10299v1 Announce Type: new Abstract: Recent advances in large-scale multimodal models have drivenremarkable progress in vision-language tasks; however, comprehensiveomni-modal understanding remains under-explored, largely due to thescarcity of datasets with rich, explicitly aligned auditory cues.