7 citations · 15 across the 15 of their papers we have counts for
6 papers · 1 filter
Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
Rui Chen, Jianfeng Zhang, Yixun Liang +7
Recent 3D content generation pipelines commonly employ Variational Autoencoders (VAEs) to encode shapes into compact latent representations for diffusion-based generation. However,…
High Quality Human Image Animation using Regional Supervision and Motion Blur Condition
Zhongcong Xu, Chaoyue Song, Guoxian Song +8
Recent advances in video diffusion models have enabled realistic and controllable human image animation with temporal coherence. Although generating reasonable results, existing me…
Empowering Visual Creativity: A Vision-Language Assistant to Image Editing Recommendations
Tiancheng Shen, Jun Hao Liew, Long Mai +3
Advances in text-based image generation and editing have revolutionized content creation, enabling users to create impressive content from imaginative text prompts. However, existi…
LightningDrag: Lightning Fast and Accurate Drag-based Image Editing Emerging from Videos
Yujun Shi, Jun Hao Liew, Hanshu Yan +2
Accuracy and speed are critical in image editing tasks. Pan et al. introduced a drag-based image editing framework that achieves pixel-level control using Generative Adversarial Ne…
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
Hanshu Yan, Xingchao Liu, Jiachun Pan +3
We present Piecewise Rectified Flow (PeRFlow), a flow-based method for accelerating diffusion models. PeRFlow divides the sampling process of generative flows into several time win…
Magic-Boost: Boost 3D Generation with Multi-View Conditioned Diffusion
Fan Yang, Jianfeng Zhang, Yichun Shi +7
Benefiting from the rapid development of 2D diffusion models, 3D content generation has witnessed significant progress. One promising solution is to finetune the pre-trained 2D dif…