activity
20242026
collaborators

8 papers

cs.SD2026

CoSyncDiT: Cognitive Synchronous Diffusion Transformer for Movie Dubbing

Gaoxiang Cong, Liang Li, Jiaxin Ye +4

Movie dubbing aims to synthesize speech that preserves the vocal identity of a reference audio while synchronizing with the lip movements in a target video. Existing methods fail t…

cs.CV2026

Exploring the Temporal Consistency for Point-Level Weakly-Supervised Temporal Action Localization

Yunchuan Ma, Laiyun Qing, Guorong Li +3

Point-supervised Temporal Action Localization (PTAL) adopts a lightly frame-annotated paradigm (\textit{i.e.}, labeling only a single frame per action instance) to train a model to…

cs.CV2026

Boosting Point-supervised Temporal Action Localization via Text Refinement and Alignment

Yunchuan Ma, Laiyun Qing, Guorong Li +3

Recently, point-supervised temporal action localization has gained significant attention for its effective balance between labeling costs and localization accuracy. However, curren…

cs.MM2025

FlowDubber: Movie Dubbing with LLM-based Semantic-aware Learning and Flow Matching based Voice Enhancing

Gaoxiang Cong, Liang Li, Jiadong Pan +5

Movie Dubbing aims to convert scripts into speeches that align with the given movie clip in both temporal and emotional aspects while preserving the vocal timbre of a given brief r…

cs.CV2025

SDVPT: Semantic-Driven Visual Prompt Tuning for Open-World Object Counting

Yiming Zhao, Guorong Li, Laiyun Qing +5

Open-world object counting leverages the robust text-image alignment of pre-trained vision-language models (VLMs) to enable counting of arbitrary categories in images specified by…

cs.CV2025

The Devil is in the Distributions: Explicit Modeling of Scene Content is Key in Zero-Shot Video Captioning

Mingkai Tian, Guorong Li, Yuankai Qi +4

Zero-shot video captioning requires that a model generate high-quality captions without human-annotated video-text pairs for training. State-of-the-art approaches to the problem le…