12 citations · 23 across the 9 of their papers we have counts for
10 papers
Vorch-Streamer: Extending Human Audio-Visual Generation to Real-Time Long-Form Streaming
Menglin Han, Yang Ding, Yulei Lu +6
Real-time long-form avatar audio-video generation requires causal, continuous synthesis while maintaining audiovisual synchronization and visual consistency. Adapting a pretrained…
Vorch-Human: Unified Multi-Task Human-Centric Generation via Long-Horizon Continuation
Yang Ding, Haoran Yu, Xin Ma +8
Human-centric audio-visual generation spans several closely related tasks: animating a person from driving speech, jointly generating speech and video from a voice reference, and s…
Vorch-Omni: Multi-Task Orchestration of Sight and Sound
Vorch Team, Xiaoyu Chen, Yang Ding +25
Recent advances in generative video modeling have enabled diverse generation, reference-based synthesis, extension, and editing, but existing approaches often rely on fragmented ta…
Vorch-Director: Interactive World Story Model via Noise-Aware Error Rectification
Lisai Zhang, Yidi Wu, Qi Liu +7
Autoregressive continuation provides a natural path toward minute-scale audio-visual generation by repeatedly extending a short-window generator conditioned on previously generated…
Vorch-IR: Long-Form Unified Multimodal Identity Replacement Video Generation
Yaole Wang, Xiaoyu Chen, Xin Ma +5
Video identity replacement seeks to transfer the identities of one or more subjects while preserving the motion, expressions, and temporal structure of a driving video. Existing me…
Monocular Normal Estimation via Shading Sequence Estimation
Zongrui Li, Xinhua Ma, Minghui Hu +6
Monocular normal estimation aims to estimate the normal map from a single RGB image of an object under arbitrary lights. Existing methods rely on deep models to directly predict no…
Training-free Stylized Text-to-Image Generation with Fast Inference
Xin Ma, Yaohui Wang, Xinyuan Chen +2
Although diffusion models exhibit impressive generative capabilities, existing methods for stylized image generation based on these models often require textual inversion or fine-t…
Cinemo: Consistent and Controllable Image Animation with Motion Diffusion Models
Xin Ma, Yaohui Wang, Gengyun Jia +4
Diffusion models have achieved great progress in image animation due to powerful generative capabilities. However, maintaining spatio-temporal consistency with detailed information…
Latte: Latent Diffusion Transformer for Video Generation
Xin Ma, Yaohui Wang, Xinyuan Chen +5
We propose Latte, a novel Latent Diffusion Transformer for video generation. Latte first extracts spatio-temporal tokens from input videos and then adopts a series of Transformer b…
SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction
Xinyuan Chen, Yaohui Wang, Lingjun Zhang +7
Recently video generation has achieved substantial progress with realistic results. Nevertheless, existing AI-generated videos are usually very short clips ("shot-level") depicting…