4 papers · 1 filter
LoST: Level of Semantics Tokenization for 3D Shapes
Niladri Shekhar Dutt, Zifan Shi, Paul Guerrero +4
Tokenization is a fundamental technique in the generative modeling of various modalities. In particular, it plays a critical role in autoregressive (AR) models, which have recently…
Temporal Residual Jacobians For Rig-free Motion Transfer
Sanjeev Muralikrishnan, Niladri Shekhar Dutt, Siddhartha Chaudhuri +4
We introduce Temporal Residual Jacobians as a novel representation to enable data-driven motion transfer. Our approach does not assume access to any rigging or intermediate shape k…
ProteusNeRF: Fast Lightweight NeRF Editing using 3D-Aware Image Context
Binglun Wang, Niladri Shekhar Dutt, Niloy J. Mitra
Neural Radiance Fields (NeRFs) have recently emerged as a popular option for photo-realistic object capture due to their ability to faithfully capture high-fidelity volumetric cont…
Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features
Niladri Shekhar Dutt, Sanjeev Muralikrishnan, Niloy J. Mitra
We present Diff3F as a simple, robust, and class-agnostic feature descriptor that can be computed for untextured input shapes (meshes or point clouds). Our method distills diffusio…