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20182023
most citedCollaborative Unsupervised Domain Adaptation for Medical Image Diagnosis

192 citations · 709 across the 45 of their papers we have counts for

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45 papers · 1 filter

cs.CV2023

Likelihood-Based Text-to-Image Evaluation with Patch-Level Perceptual and Semantic Credit Assignment

Qi Chen, Chaorui Deng, Zixiong Huang +3

Text-to-image synthesis has made encouraging progress and attracted lots of public attention recently. However, popular evaluation metrics in this area, like the Inception Score an…

cs.CV20231 cited

Nav: Action-Aware Zero-Shot Robot Navigation by Exploiting Vision-and-Language Ability of Foundation Models

Peihao Chen, Xinyu Sun, Hongyan Zhi +5

We study the task of zero-shot vision-and-language navigation (ZS-VLN), a practical yet challenging problem in which an agent learns to navigate following a path described by langu…

cs.CV20231 cited

Cross-Ray Neural Radiance Fields for Novel-view Synthesis from Unconstrained Image Collections

Yifan Yang, Shuhai Zhang, Zixiong Huang +2

Neural Radiance Fields (NeRF) is a revolutionary approach for rendering scenes by sampling a single ray per pixel and it has demonstrated impressive capabilities in novel-view synt…

cs.CV2023

Learning Vision-and-Language Navigation from YouTube Videos

Kunyang Lin, Peihao Chen, Diwei Huang +3

Vision-and-language navigation (VLN) requires an embodied agent to navigate in realistic 3D environments using natural language instructions. Existing VLN methods suffer from train…

cs.CV20232 cited

CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation

Lizhao Liu, Zhuangwei Zhuang, Shangxin Huang +5

We study the task of weakly-supervised point cloud semantic segmentation with sparse annotations (e.g., less than 0.1% points are labeled), aiming to reduce the expensive cost of d…

cs.CV2023

Imbalance-Agnostic Source-Free Domain Adaptation via Avatar Prototype Alignment

Hongbin Lin, Mingkui Tan, Yifan Zhang +5

Source-free Unsupervised Domain Adaptation (SF-UDA) aims to adapt a well-trained source model to an unlabeled target domain without access to the source data. One key challenge is…