← Search

Niladri Shekhar Dutt

3 accepted papers

2026

LoST: Level of Semantics Tokenization for 3D Shapes

CVPR 2026

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 emerged as a compelling option for 3D generation.However, optimal tokenization of 3D shapes remains an open question. S

Cited by 0SourcecodeScholar
2024

Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features

CVPR 2024poster

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 diffusion features from image foundational models onto input shapes. Specifically we use the input shapes to produce depth and nor…

2024

Temporal Residual Jacobians for Rig-free Motion Transfer

ECCV 2024poster

"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 keyframes, produces geometrically and temporally consistent motions, and can be used to transfer long motion sequences.…