8 citations · 10 across the 21 of their papers we have counts for
8 papers · 1 filter
PoseAnything: Universal Pose-guided Video Generation with Part-aware Temporal Coherence
Ruiyan Wang, Teng Hu, Kaihui Huang +3
Pose-guided video generation refers to controlling the motion of subjects in generated video through a sequence of poses. It enables precise control over subject motion and has imp…
InstanceV: Instance-Level Video Generation
Yuheng Chen, Teng Hu, Jiangning Zhang +3
Recent advances in text-to-video diffusion models have enabled the generation of high-quality videos conditioned on textual descriptions. However, most existing text-to-video model…
Harmony: Harmonizing Audio and Video Generation through Cross-Task Synergy
Teng Hu, Zhentao Yu, Guozhen Zhang +6
The synthesis of synchronized audio-visual content is a key challenge in generative AI, with open-source models facing challenges in robust audio-video alignment. Our analysis reve…
UltraGen: High-Resolution Video Generation with Hierarchical Attention
Teng Hu, Jiangning Zhang, Zihan Su +1
Recent advances in video generation have made it possible to produce visually compelling videos, with wide-ranging applications in content creation, entertainment, and virtual real…
IAR2: Improving Autoregressive Visual Generation with Semantic-Detail Associated Token Prediction
Ran Yi, Teng Hu, Zihan Su +2
Autoregressive models have emerged as a powerful paradigm for visual content creation, but often overlook the intrinsic structural properties of visual data. Our prior work, IAR, i…
PolyVivid: Vivid Multi-Subject Video Generation with Cross-Modal Interaction and Enhancement
Teng Hu, Zhentao Yu, Zhengguang Zhou +4
Despite recent advances in video generation, existing models still lack fine-grained controllability, especially for multi-subject customization with consistent identity and intera…
Image Inversion: A Survey from GANs to Diffusion and Beyond
Yinan Chen, Jiangning Zhang, Yali Bi +6
Image inversion is a fundamental task in generative models, aiming to map images back to their latent representations to enable downstream applications such as editing, restoration…
Improving Autoregressive Visual Generation with Cluster-Oriented Token Prediction
Teng Hu, Jiangning Zhang, Ran Yi +5
Employing LLMs for visual generation has recently become a research focus. However, the existing methods primarily transfer the LLM architecture to visual generation but rarely inv…