29 citations · 106 across the 11 of their papers we have counts for
16 papers · 1 filter
3D-Aware Encoding for Style-based Neural Radiance Fields
Yu-Jhe Li, Tao Xu, Bichen Wu +6
We tackle the task of NeRF inversion for style-based neural radiance fields, (e.g., StyleNeRF). In the task, we aim to learn an inversion function to project an input image to the…
Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation
Ruizhe Cheng, Bichen Wu, Peizhao Zhang +2
Traditional computer vision models are trained to predict a fixed set of predefined categories. Recently, natural language has been shown to be a broader and richer source of super…
Unbiased Teacher for Semi-Supervised Object Detection
Yen-Cheng Liu, Chih-Yao Ma, Zijian He +6
Semi-supervised learning, i.e., training networks with both labeled and unlabeled data, has made significant progress recently. However, existing works have primarily focused on im…
One Shot 3D Photography
Johannes Kopf, Kevin Matzen, Suhib Alsisan +12
3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving…
Geometric Correspondence Fields: Learned Differentiable Rendering for 3D Pose Refinement in the Wild
Alexander Grabner, Yaming Wang, Peizhao Zhang +5
We present a novel 3D pose refinement approach based on differentiable rendering for objects of arbitrary categories in the wild. In contrast to previous methods, we make two main…
Visual Transformers: Token-based Image Representation and Processing for Computer Vision
Bichen Wu, Chenfeng Xu, Xiaoliang Dai +7
Computer vision has achieved remarkable success by (a) representing images as uniformly-arranged pixel arrays and (b) convolving highly-localized features. However, convolutions tr…