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20242026
most citedExploring the latent space of diffusion models directly through singular value decomposition

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Entropy-Guided k-Guard Sampling for Long-Horizon Autoregressive Video Generation

Yizhao Han, Tianxing Shi, Zhao Wang +6

Autoregressive (AR) architectures have achieved significant successes in LLMs, inspiring explorations for video generation. In LLMs, top-p/top-k sampling strategies work exceptiona…

cs.CV2025

LLIA -- Enabling Low-Latency Interactive Avatars: Real-Time Audio-Driven Portrait Video Generation with Diffusion Models

Haojie Yu, Zhaonian Wang, Yihan Pan +7

Diffusion-based models have gained wide adoption in the virtual human generation due to their outstanding expressiveness. However, their substantial computational requirements have…

cs.CV2025★ 1 cited

Exploring the latent space of diffusion models directly through singular value decomposition

Li Wang, Boyan Gao, Yanran Li +4

Despite the groundbreaking success of diffusion models in generating high-fidelity images, their latent space remains relatively under-explored, even though it holds significant pr…

cs.CV2024

ViMo: Generating Motions from Casual Videos

Liangdong Qiu, Chengxing Yu, Yanran Li +6

Although humans have the innate ability to imagine multiple possible actions from videos, it remains an extraordinary challenge for computers due to the intricate camera movements…

cs.CV2024

Tunnel Try-on: Excavating Spatial-temporal Tunnels for High-quality Virtual Try-on in Videos

Zhengze Xu, Mengting Chen, Zhao Wang +6

Video try-on is a challenging task and has not been well tackled in previous works. The main obstacle lies in preserving the details of the clothing and modeling the coherent motio…