Search Results for author: Kyle Sargent

Found 6 papers, 1 papers with code

ZeroNVS: Zero-Shot 360-Degree View Synthesis from a Single Image

no code implementations27 Oct 2023 Kyle Sargent, Zizhang Li, Tanmay Shah, Charles Herrmann, Hong-Xing Yu, Yunzhi Zhang, Eric Ryan Chan, Dmitry Lagun, Li Fei-Fei, Deqing Sun, Jiajun Wu

Further, we observe that Score Distillation Sampling (SDS) tends to truncate the distribution of complex backgrounds during distillation of 360-degree scenes, and propose "SDS anchoring" to improve the diversity of synthesized novel views.

Novel View Synthesis

VQ3D: Learning a 3D-Aware Generative Model on ImageNet

no code implementations ICCV 2023 Kyle Sargent, Jing Yu Koh, Han Zhang, Huiwen Chang, Charles Herrmann, Pratul Srinivasan, Jiajun Wu, Deqing Sun

Recent work has shown the possibility of training generative models of 3D content from 2D image collections on small datasets corresponding to a single object class, such as human faces, animal faces, or cars.

Position

Self-supervised AutoFlow

no code implementations CVPR 2023 Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun

Recently, AutoFlow has shown promising results on learning a training set for optical flow, but requires ground truth labels in the target domain to compute its search metric.

Optical Flow Estimation

Pyramid Adversarial Training Improves ViT Performance

1 code implementation CVPR 2022 Charles Herrmann, Kyle Sargent, Lu Jiang, Ramin Zabih, Huiwen Chang, Ce Liu, Dilip Krishnan, Deqing Sun

In this work, we present pyramid adversarial training (PyramidAT), a simple and effective technique to improve ViT's overall performance.

Ranked #9 on Domain Generalization on ImageNet-C (using extra training data)

Adversarial Attack Data Augmentation +2

SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting

no code implementations ICCV 2021 Varun Jampani, Huiwen Chang, Kyle Sargent, Abhishek Kar, Richard Tucker, Michael Krainin, Dominik Kaeser, William T. Freeman, David Salesin, Brian Curless, Ce Liu

We present SLIDE, a modular and unified system for single image 3D photography that uses a simple yet effective soft layering strategy to better preserve appearance details in novel views.

Image Matting

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