6 citations · 15 across the 13 of their papers we have counts for
15 papers
P-CORE: Self-Supervised Surface Consistency for Point-Based Neural Editing
Yanshu Zhang, Shichong Peng, Mehran Aghabozorgi +2
Advances in neural rendering have enabled high-fidelity multi-view reconstruction of 3D scenes. However, free-form non-rigid shape editing remains a significant challenge. Point-ba…
RigPAPR: Rig-Based Animation of Static Neural Point Clouds from a Fixed-Viewpoint Video
Shichong Peng, Yanshu Zhang, Ke Li
Static neural point reconstructions capture a subject at high fidelity from posed images. Given such a reconstruction, we aim to animate it to follow a monocular fixed-viewpoint dr…
Latent Dynamics for Full Body Avatar Animation
Shichong Peng, Chengxiang Yin, Fei Jiang +7
Pose-driven full-body avatars built on neural rendering produce high-quality novel views of a captured subject. Yet loose clothing and other dynamic elements deform in ways pose al…
Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis
Chirag Vashist, Shichong Peng, Ke Li
An emerging area of research aims to learn deep generative models with limited training data. Prior generative models like GANs and diffusion models require a lot of data to perfor…
Intrinsic PAPR: Tackling Misattribution in 3D Intrinsic Decomposition via Proximity Attention Point Rendering
Alireza Moazeni, Shichong Peng, Yanshu Zhang +2
Recent point-based intrinsic decomposition and inverse rendering methods have advanced the modelling of the shading and albedo of 3D scenes. However, we identify a fundamental limi…
PAPR in Motion: Seamless Point-level 3D Scene Interpolation
Shichong Peng, Yanshu Zhang, Ke Li
We propose the problem of point-level 3D scene interpolation, which aims to simultaneously reconstruct a 3D scene in two states from multiple views, synthesize smooth point-level i…
How Good Are Deep Generative Models for Solving Inverse Problems?
Shichong Peng, Alireza Moazeni, Ke Li
Deep generative models, such as diffusion models, GANs, and IMLE, have shown impressive capability in tackling inverse problems. However, the validity of model-generated solutions…
PAPR: Proximity Attention Point Rendering
Yanshu Zhang, Shichong Peng, Alireza Moazeni +1
Learning accurate and parsimonious point cloud representations of scene surfaces from scratch remains a challenge in 3D representation learning. Existing point-based methods often…
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis
Shichong Peng, Alireza Moazeni, Ke Li
A persistent challenge in conditional image synthesis has been to generate diverse output images from the same input image despite only one output image being observed per input im…
Multimodal Shape Completion via IMLE
Himanshu Arora, Saurabh Mishra, Shichong Peng +2
Shape completion is the problem of completing partial input shapes such as partial scans. This problem finds important applications in computer vision and robotics due to issues su…
Cascading Modular Network (CAM-Net) for Multimodal Image Synthesis
Shichong Peng, Alireza Moazeni, Ke Li
Deep generative models such as GANs have driven impressive advances in conditional image synthesis in recent years. A persistent challenge has been to generate diverse versions of…
Generating Unobserved Alternatives
Shichong Peng, Ke Li
We consider problems where multiple predictions can be considered correct, but only one of them is given as supervision. This setting differs from both the regression and class-con…
Better Knowledge Retention through Metric Learning
Ke Li, Shichong Peng, Kailas Vodrahalli +1
In continual learning, new categories may be introduced over time, and an ideal learning system should perform well on both the original categories and the new categories. While de…
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation
Ke Li, Shichong Peng, Tianhao Zhang +1
Many tasks in computer vision and graphics fall within the framework of conditional image synthesis. In recent years, generative adversarial nets (GANs) have delivered impressive a…
Super-Resolution via Conditional Implicit Maximum Likelihood Estimation
Ke Li, Shichong Peng, Jitendra Malik
Single-image super-resolution (SISR) is a canonical problem with diverse applications. Leading methods like SRGAN produce images that contain various artifacts, such as high-freque…