7 papers
Uni3C: Unifying Precisely 3D-Enhanced Camera and Human Motion Controls for Video Generation
Chenjie Cao, Jingkai Zhou, Shikai Li +5
Camera and human motion controls have been extensively studied for video generation, but existing approaches typically address them separately, suffering from limited data with hig…
RealisMotion: Decomposed Human Motion Control and Video Generation in the World Space
Jingyun Liang, Jingkai Zhou, Shikai Li +5
Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control ov…
RealisVSR: Detail-enhanced Diffusion for Real-World 4K Video Super-Resolution
Weisong Zhao, Jingkai Zhou, Xiangyu Zhu +4
Video Super-Resolution (VSR) has achieved significant progress through diffusion models, effectively addressing the over-smoothing issues inherent in GAN-based methods. Despite rec…
On Denoising Walking Videos for Gait Recognition
Dongyang Jin, Chao Fan, Jingzhe Ma +3
To capture individual gait patterns, excluding identity-irrelevant cues in walking videos, such as clothing texture and color, remains a persistent challenge for vision-based gait…
RealisDance-DiT: Simple yet Strong Baseline towards Controllable Character Animation in the Wild
Jingkai Zhou, Yifan Wu, Shikai Li +5
Controllable character animation remains a challenging problem, particularly in handling rare poses, stylized characters, character-object interactions, complex illumination, and d…
RealisHuman: A Two-Stage Approach for Refining Malformed Human Parts in Generated Images
Benzhi Wang, Jingkai Zhou, Jingqi Bai +4
In recent years, diffusion models have revolutionized visual generation, outperforming traditional frameworks like Generative Adversarial Networks (GANs). However, generating image…