3 × 2: 3D Object Part Segmentation by 2D Semantic Correspondences

Leveraging visual correspondence from off the shelf vision foundation models for 3D part segmentation.

Anh Thai, Weiyao Wang, Hao Tang, Stefan Stojanov, James M. Rehg, Matt Feiszli.

ECCV 2024 - poster

paper

ZeroShape: Regression-based Zero-shot Shape Reconstruction

SOTA 3D shape reconstructor with high computational efficiency and low training data budget.

Zixuan Huang*, Stefan Stojanov*, Anh Thai, Varun Jampani, James M. Rehg

CVPR 2024 - poster

paper / code / project page / demo

Low-shot Object Learning with Mutual Exclusivity Bias

Mutual Exclusivity Bias enables fast learning of objects that generalizes.

Anh Thai, Ahmad Humayun, Stefan Stojanov, Zixuan Huang, Bikram Boote, James M. Rehg

NeurIPS 2023, Datasets and Benchmarks Track

paper / code / project page

ShapeClipper: Scalable 3D Shape Learning via Geometric and CLIP-based Consistency

CLIP and geometric consistency constraints facilitate scalable learning of object shape reconstruction.

Zixuan Huang, Varun Jampani, Anh Thai, Yuanzhen Li, Stefan Stojanov, James M. Rehg

CVPR 2023 - poster

arxiv / code / project page / video

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

Dense feature-level self-supervised learning from multiple camera views without
any category labels leads to representations that can generalize to novel categories.

Stefan Stojanov, Anh Thai, Zixuan Huang, James M. Rehg

NeurIPS 2022 - Poster

arxiv / code / project page / poster / video

Planes vs. Chairs: Category-guided 3D shape learning without any 3D cues

A 3D-unsupervised model that learn shapes of multiple object categories at once.

Zixuan Huang, Stefan Stojanov, Anh Thai, Varun Jampani, James M. Rehg

ECCV 2022 - Poster

arxiv / code / project page / poster / video

The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction

Continual learning of 3D shape reconstruction does not suffer from catastrophic
forgetting as much as discriminative learning tasks.

Anh Thai, Stefan Stojanov, Zixuan Huang, James M. Rehg

3DV 2022 - Poster

arxiv / code

The Benefits of Depth Information for Head-Mounted Gaze Estimation

Fusing depth and image information improves deep models' robustness
to fitment and slip for head mounted gaze estimation

Stefan Stojanov, Sachin Talathi, Abhishek Sharma

ETRA 2022 - Short Paper

pdf

Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Bias

Learning representations to generalize based on 3D shape and then learning
to map images into them leads to improved low-shot generalization.

Stefan Stojanov, Anh Thai, James M. Rehg

CVPR 2021 - Poster

arxiv / code / dataset / project page

3D Reconstruction of Novel Object Shapes from Single Images

An implicit SDF representation-based method for single view 3D shape reconstruction

Anh Thai*, Stefan Stojanov*, James M. Rehg

3DV 2021 - Oral

arxiv / code / project page

Incremental Object Learning from Contiguous Views

Repetition of learned concepts in continual learning ameliorates catastrophic forgettng.

Stefan Stojanov, Anh Thai*, Samarth Mishra*, James M. Rehg

CVPR 2019 - Oral - Best paper award finalist

pdf / code / dataset / project page / video

Unsupervised 3D Pose Estimation with Geometric Self-supervision

Utilizing adversarial learning to estimate 3D human pose without 3D supervision.

Ching-Hang Chen, Ambrish Tyagi, Amit Agrawal, Dylan Drover, Stefan Stojanov, James M. Rehg

CVPR 2019 - Poster

arxiv