activity
20172022
most citedUncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

280 citations · 650 across the 15 of their papers we have counts for

collaborators

30 papers

cs.CV20222 cited

1st Place Solution of The Robust Vision Challenge 2022 Semantic Segmentation Track

Junfei Xiao, Zhichao Xu, Shiyi Lan +3

This report describes the winning solution to the Robust Vision Challenge (RVC) semantic segmentation track at ECCV 2022. Our method adopts the FAN-B-Hybrid model as the encoder an…

cs.CV2022112 cited

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Manli Shu, Weili Nie, De-An Huang +4

Pre-trained vision-language models (e.g., CLIP) have shown promising zero-shot generalization in many downstream tasks with properly designed text prompts. Instead of relying on ha…

cs.CV202287 cited

MBEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation

Enze Xie, Zhiding Yu, Daquan Zhou +5

In this paper, we propose MBEV, a unified framework that jointly performs 3D object detection and map segmentation in the Birds Eye View~(BEV) space with multi-camera image inp…

cs.CV2022

CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs

Jiteng Mu, Shalini De Mello, Zhiding Yu +4

Recent advances show that Generative Adversarial Networks (GANs) can synthesize images with smooth variations along semantically meaningful latent directions, such as pose, express…

cs.CV20223 cited

FreeSOLO: Learning to Segment Objects without Annotations

Xinlong Wang, Zhiding Yu, Shalini De Mello +4

Instance segmentation is a fundamental vision task that aims to recognize and segment each object in an image. However, it requires costly annotations such as bounding boxes and se…

cs.LG202249 cited

Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions

Jiachen Sun, Qingzhao Zhang, Bhavya Kailkhura +3

Deep neural networks on 3D point cloud data have been widely used in the real world, especially in safety-critical applications. However, their robustness against corruptions is le…