collaborators

11 papers

cs.CV2026

SR-Edit: Region-Aware Image Editing via Self-Refinement

Andong Wang, Zehua Chen, Yuxuan Jiang +1

With the recent rapid progress in generative models, image editing has made remarkable advances, yet achieving faithful edits that precisely modify only the target regions while st…

eess.AS2026

CineDub: Scaling End-to-End Video Dubbing to Multi-Speaker Dialogues with Coherent Sound Effects

Yusheng Dai, Kangdi Wang, Baolong Gao +4

Automatic video dubbing in the wild remains fundamentally limited by two competing constraints: hierarchical methods depend on brittle, multi-stage preprocessing pipelines that sev…

cs.CV2026

Visual Representation Matters: Exploiting Temporal Differences in Video-to-Audio Generation

Zehua Chen, Junyou Wang, Yuxuan Jiang +5

Video-to-audio (V2A) generation extends image-to-audio generation (I2A) by introducing consecutive frames that provide essential temporal cues for audio synthesis. However, existin…

cs.CV2026

Vidu S1: A Real-Time Interactive Video Generation Model

Jintao Zhang, Kai Jiang, Jintao Chen +24

We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment throug…

cs.CV2026

AV-SyncBench: Decoupled Benchmarking of Temporal and Semantic Audio-Visual Synchronization

Tianhong Zhou, Mingyang Han, Boyu Li +8

Audio-visual feature extraction is a fundamental component of multimodal understanding and generation tasks. However, existing evaluation protocols for feature extraction models ex…

cs.SD2026

FreeSonic: Training-Free Temporal-Aware Decoupled Attention for Precise Audio Editing

Yuxuan Jiang, Mingyang Han, Yusheng Dai +12

Text-to-audio (TTA) generation has made significant strides, yet achieving precise and consistent audio editing remains a major challenge. However, existing methods struggle to bal…

cs.AI2026

QA-MoE: Towards a Continuous Reliability Spectrum with Quality-Aware Mixture of Experts for Robust Multimodal Sentiment Analysis

Yitong Zhu, Yuxuan Jiang, Guanxuan Jiang +4

Multimodal Sentiment Analysis (MSA) aims to infer human sentiment from textual, acoustic, and visual signals. In real-world scenarios, however, multimodal inputs are often compromi…

cs.SD2026

Omni2Sound: Towards Unified Video-Text-to-Audio Generation

Yusheng Dai, Zehua Chen, Yuxuan Jiang +4

Training a unified model integrating video-to-audio (V2A), text-to-audio (T2A), and joint video-text-to-audio (VT2A) generation offers significant application flexibility, yet face…

cs.SD2025

ControlAudio: Tackling Text-Guided, Timing-Indicated and Intelligible Audio Generation via Progressive Diffusion Modeling

Yuxuan Jiang, Zehua Chen, Zeqian Ju +3

Text-to-audio (TTA) generation with fine-grained control signals, e.g., precise timing control or intelligible speech content, has been explored in recent works. However, constrain…

cs.SD2025

AudioMoG: Guiding Audio Generation with Mixture-of-Guidance

Junyou Wang, Zehua Chen, Binjie Yuan +4

The design of diffusion-based audio generation systems has been investigated from diverse perspectives, such as data space, network architecture, and conditioning techniques, while…

cs.SD2025

FreeAudio: Training-Free Timing Planning for Controllable Long-Form Text-to-Audio Generation

Yuxuan Jiang, Zehua Chen, Zeqian Ju +3

Text-to-audio (T2A) generation has achieved promising results with the recent advances in generative models. However, because of the limited quality and quantity of temporally-alig…