380 citations · 923 across the 38 of their papers we have counts for
7 papers · 1 filter
Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation
Bichen Wu, Ruizhe Cheng, Peizhao Zhang +3
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…
Cross-Domain Adaptive Teacher for Object Detection
Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma +6
We address the task of domain adaptation in object detection, where there is a domain gap between a domain with annotations (source) and a domain of interest without annotations (t…
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run
Bichen Wu, Chaojian Li, Hang Zhang +6
Neural Architecture Search (NAS) has been widely adopted to design accurate and efficient image classification models. However, applying NAS to a new computer vision task still req…
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models
Chenfeng Xu, Shijia Yang, Tomer Galanti +7
3D point-clouds and 2D images are different visual representations of the physical world. While human vision can understand both representations, computer vision models designed fo…
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…
You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module
Chenfeng Xu, Bohan Zhai, Bichen Wu +5
3D point-cloud-based perception is a challenging but crucial computer vision task. A point-cloud consists of a sparse, unstructured, and unordered set of points. To understand a po…
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…