activity
20242026
most citedAudio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing

1 citations · 1 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2026

DRM: Diffusion-based Reward Model With Step-wise Guidance

Jaxon Zhang, Binxin Yang, Hubery Yin +2

Current mainstream methods of aligning diffusion models with human preferences typically employ VLM-based reward models. However, these reward models, pre-trained for semantic alig…

cs.CV2026

OmniHuman: A Large-scale Dataset and Benchmark for Human-Centric Video Generation

Lei Zhu, Xing Cai, Yingjie Chen +6

Recent advancements in audio-video joint generation models have demonstrated impressive capabilities in content creation. However, generating high-fidelity human-centric videos in…

cs.CV2026

VersusQ: Pairwise Margin Reasoning for Generalizable Video Quality Assessment

Shibei Meng, Binxin Yang, Yuan Liu +4

Large Multimodal Models (LMMs) have shown promise for video quality assessment, but most methods still predict an absolute score for each video. Such pointwise supervision often mi…

cs.SD2026★ 1 cited

Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing

Zeyue Tian, Binxin Yang, Zhaoyang Liu +8

Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typically addressed by specialized…

cs.CV2026

NOVA: Sparse Control, Dense Synthesis for Pair-Free Video Editing

Tianlin Pan, Jiayi Dai, Chenpu Yuan +7

Recent video editing models have achieved impressive results, but most still require large-scale paired datasets. Collecting such naturally aligned pairs at scale remains highly ch…

cs.CV2026

Identity as Presence: Towards Appearance and Voice Personalized Joint Audio-Video Generation

Qin Chen, Yingjie Chen, Shilun Lin +9

Recent advances in video synthesis have enabled realistic integration of real individuals, driving demand for identity-aware generation. While emerging methods support joint appear…

cs.CV2026

StableWorld: Towards Stable and Consistent Long Interactive Video Generation

Ying Yang, Zhengyao Lv, Yujia Zeng +9

In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic and controllable video worlds th…

cs.CV2025

DiverseAR: Boosting Diversity in Bitwise Autoregressive Image Generation

Ying Yang, Zhengyao Lv, Tianlin Pan +5

In this paper, we investigate the underexplored challenge of sample diversity in autoregressive (AR) generative models with bitwise visual tokenizers. We first analyze the factors…

cs.CV2025

Video-GPT via Next Clip Diffusion

Shaobin Zhuang, Zhipeng Huang, Ying Zhang +6

GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alte…

cs.CV2025

WeGen: A Unified Model for Interactive Multimodal Generation as We Chat

Zhipeng Huang, Shaobin Zhuang, Canmiao Fu +7

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack th…

cs.CV2025

Get In Video: Add Anything You Want to the Video

Shaobin Zhuang, Zhipeng Huang, Binxin Yang +7

Video editing increasingly demands the ability to incorporate specific real-world instances into existing footage, yet current approaches fundamentally fail to capture the unique v…

cs.SD2024

VidMusician: Video-to-Music Generation with Semantic-Rhythmic Alignment via Hierarchical Visual Features

Sifei Li, Binxin Yang, Chunji Yin +4

Video-to-music generation presents significant potential in video production, requiring the generated music to be both semantically and rhythmically aligned with the video. Achievi…