PrEditor3D: Fast and Precise 3D Shape Editing (arxiv)
A feed-forward 3D local editing tool that can edit a 3D mesh within 2 minutes.
4Real-Video: Learning Generalizable Photo-Realistic 4D Video Diffusion (arxiv)
A large-scale video diffusion model that can generate 4D video grids in a feed-forward manner.
GTR: Improving Large 3D Re- construction Models through Geometry and Texture Refinemen (ICLR 2025)
A large-scale multi-view images to 3D mesh reconsutrction for objects.
DELTA: Dense Efficient Long-range 3D Tracking for any video (ICLR 2025)
Dense (per-pixel) 3D trakcking from monocular videos.
4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models (NeurIPS 2024)
The first photorealistic text-to-4D scene generation pipeline, with the use of video diffusion models.
SceneWiz3D: Towards Text-guided 3D Scene Composition (CVPR 2024)
High-fidelity 3D scene generation from text.
HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance (ICLR 2024)
A high-fidelity text-to-3D generation model with pretrained text-to-image models as prior.
Diffusion probabilistic fields (ICLR 2023)
A diffusion model that learns distributions over continuous functions defined over metric spaces as fields.
Controllable radiance fields for dynamic face synthesis (3DV 2022)
A Controllable Radiance Field that can generate dynamic faces and human bodies with user control.
EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision (MLHC 2022)
A multi-modal X-ray generative model that is trained in a self-supervised way.
AMICO: Amodal Instance Composition (BMVC 2021)
An image composition model that can blend imperfect objects onto a target image.
Controllable GANs for Image Editing via Latent Space Navigation (ICLR 2021)
A latent-space image editing work using pretrained Generative Adversarial Networks (GANs).
FMRI data augmentation via synthesis (ISBI 2019)
A Generative Adversarial Networks (GANs) specifically designed for fMRI brain data augmentation.
Synthetic Power Analyses: Empirical Evaluation and Application to Cognitive Neuroimaging (Asilomar 2019)
A methodological approach to improve statistical analysis in cognitive neuroimaging using generated datasets.
Conditional structure generation through graph variational generative adversarial nets (NeurIPS 2019)
