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

1 code implementation • 28 Nov 2023 • 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).

3D Dense Shape Correspondence 3D Part Segmentation

BLiSS: Bootstrapped Linear Shape Space

no code implementations • 4 Sep 2023 • Sanjeev Muralikrishnan, Chun-Hao Paul Huang, Duygu Ceylan, Niloy J. Mitra

Morphable models are fundamental to numerous human-centered processes as they offer a simple yet expressive shape space.

GLASS: Geometric Latent Augmentation for Shape Spaces

1 code implementation • CVPR 2022 • Sanjeev Muralikrishnan, Siddhartha Chaudhuri, Noam Aigerman, Vladimir Kim, Matthew Fisher, Niloy Mitra

We investigate the problem of training generative models on a very sparse collection of 3D models.

valid

Shape Unicode: A Unified Shape Representation

no code implementations • CVPR 2019 • Sanjeev Muralikrishnan, Vladimir G. Kim, Matthew Fisher, Siddhartha Chaudhuri

3D shapes come in varied representations from a set of points to a set of images, each capturing different aspects of the shape.

Retrieval

Tags2Parts: Discovering Semantic Regions from Shape Tags

1 code implementation • CVPR 2018 • Sanjeev Muralikrishnan, Vladimir G. Kim, Siddhartha Chaudhuri

We test our method on segmentation benchmarks and show that even with weak supervision of whole shape tags, our method can infer meaningful semantic regions, without ever observing shape segmentations.

TAG