activity
20232026
most citedSchrodinger Bridges Beat Diffusion Models on Text-to-Speech Synthesis

2 citations · 2 across the 13 of their papers we have counts for

collaborators

16 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…

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.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.CV2026

GMS-CAVP: Improving Audio-Video Correspondence with Multi-Scale Contrastive and Generative Pretraining

Shentong Mo, Zehua Chen, Jun Zhu

Recent advances in video-audio (V-A) understanding and generation have increasingly relied on joint V-A embeddings, which serve as the foundation for tasks such as cross-modal retr…

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

VoiceBridge: General Speech Restoration with One-step Latent Bridge Models

Chi Zhang, Kaiwen Zheng, Zehua Chen +1

Bridge models have been investigated in speech enhancement but are mostly single-task, with constrained general speech restoration (GSR) capability. In this work, we propose VoiceB…

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

Audio Super-Resolution with Latent Bridge Models

Chang Li, Zehua Chen, Liyuan Wang +1

Audio super-resolution (SR), i.e., upsampling the low-resolution (LR) waveform to the high-resolution (HR) version, has recently been explored with diffusion and bridge models, whi…

eess.AS2025

Deep Learning for Personalized Binaural Audio Reproduction

Xikun Lu, Yunda Chen, Zehua Chen +6

Personalized binaural audio reproduction is the basis of realistic spatial localization, sound externalization, and immersive listening, directly shaping user experience and listen…

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…

cs.LG2025

Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer

Zehua Chen, Yuyang Miao, Liyuan Wang +3

Cardiovascular signals such as photoplethysmography (PPG), electrocardiography (ECG), and blood pressure (BP) are inherently correlated and complementary, together reflecting the h…

cs.CV2025

DiffGAP: A Lightweight Diffusion Module in Contrastive Space for Bridging Cross-Model Gap

Shentong Mo, Zehua Chen, Fan Bao +1

Recent works in cross-modal understanding and generation, notably through models like CLAP (Contrastive Language-Audio Pretraining) and CAVP (Contrastive Audio-Visual Pretraining),…

cs.SD2025

Bridge-SR: Schrödinger Bridge for Efficient SR

Chang Li, Zehua Chen, Fan Bao +1

Speech super-resolution (SR), which generates a waveform at a higher sampling rate from its low-resolution version, is a long-standing critical task in speech restoration. Previous…

cs.CV2024

FrameBridge: Improving Image-to-Video Generation with Bridge Models

Yuji Wang, Zehua Chen, Xiaoyu Chen +3

Diffusion models have achieved remarkable progress on image-to-video (I2V) generation, while their noise-to-data generation process is inherently mismatched with this task, which m…

cs.LG2023★ 2 cited

Schrodinger Bridges Beat Diffusion Models on Text-to-Speech Synthesis

Zehua Chen, Guande He, Kaiwen Zheng +2

In text-to-speech (TTS) synthesis, diffusion models have achieved promising generation quality. However, because of the pre-defined data-to-noise diffusion process, their prior dis…