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20172022
most citedSample Selection with Uncertainty of Losses for Learning with Noisy Labels

49 citations · 114 across the 17 of their papers we have counts for

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15 papers · 1 filter

cs.CV2022

Adaptive Edge-to-Edge Interaction Learning for Point Cloud Analysis

Shanshan Zhao, Mingming Gong, Xi Li +1

Recent years have witnessed the great success of deep learning on various point cloud analysis tasks, e.g., classification and semantic segmentation. Since point cloud data is spar…

cs.CV20221 cited

Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation

Yanwu Xu, Shaoan Xie, Wenhao Wu +3

Unpaired image-to-image translation (I2I) is an ill-posed problem, as an infinite number of translation functions can map the source domain distribution to the target distribution.…

cs.CV2021

Unaligned Image-to-Image Translation by Learning to Reweight

Shaoan Xie, Mingming Gong, Yanwu Xu +1

Unsupervised image-to-image translation aims at learning the mapping from the source to target domain without using paired images for training. An essential yet restrictive assumpt…

cs.CV20211 cited

Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision

Yanwu Xu, Mingming Gong, Shaoan Xie +1

Deep learning has achieved remarkable success in medicalimage segmentation, but it usually requires a large numberof images labeled with fine-grained segmentation masks, andthe ann…

cs.CV2021

Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification

Pengfei Wang, Changxing Ding, Wentao Tan +3

Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims at adapting a model trained on a labeled source domain to an unlabeled target domain. State-of-the-art obje…

cs.CV20202 cited

Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning

Huan Fu, Shunming Li, Rongfei Jia +3

Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D shape of a given 2D image from a large 3D shape database. The common routine is to map 2D images and 3D shap…