3 citations · 3 across the 5 of their papers we have counts for
5 papers
Matérn Noise for Triangulation-Agnostic Flow Matching on Meshes
Tianshu Kuai, Arman Maesumi, Daniel Ritchie +1
This paper tackles the task of learning to generate signals over triangle meshes in a triangulation-agnostic manner, meaning the trained model can be applied to different meshes an…
Towards Unsupervised Blind Face Restoration using Diffusion Prior
Tianshu Kuai, Sina Honari, Igor Gilitschenski +1
Blind face restoration methods have shown remarkable performance, particularly when trained on large-scale synthetic datasets with supervised learning. These datasets are often gen…
CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos
Tianshu Kuai, Akash Karthikeyan, Yash Kant +2
Animating an object in 3D often requires an articulated structure, e.g. a kinematic chain or skeleton of the manipulated object with proper skinning weights, to obtain smooth movem…
Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss
Anas Mahmoud, Jordan S. K. Hu, Tianshu Kuai +3
An effective framework for learning 3D representations for perception tasks is distilling rich self-supervised image features via contrastive learning. However, image-to point repr…
Point Density-Aware Voxels for LiDAR 3D Object Detection
Jordan S. K. Hu, Tianshu Kuai, Steven L. Waslander
LiDAR has become one of the primary 3D object detection sensors in autonomous driving. However, LiDAR's diverging point pattern with increasing distance results in a non-uniform sa…