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05/23/2023
Federated Generalized Category Discovery
Generalized category discovery (GCD) aims at grouping unlabeled samples ...
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05/02/2023
Boosting Adversarial Transferability via Fusing Logits of Top-1 Decomposed Feature
Recent research has shown that Deep Neural Networks (DNNs) are highly vu...
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03/30/2023
Dynamic Conceptional Contrastive Learning for Generalized Category Discovery
Generalized category discovery (GCD) is a recently proposed open-world p...
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03/28/2023
Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery
Discovering novel concepts from unlabelled data and in a continuous mann...
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03/07/2023
Logit Margin Matters: Improving Transferable Targeted Adversarial Attack by Logit Calibration
Previous works have extensively studied the transferability of adversari...
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12/18/2022
Style-Hallucinated Dual Consistency Learning: A Unified Framework for Visual Domain Generalization
Domain shift widely exists in the visual world, while modern deep neural...
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07/18/2022
Class-incremental Novel Class Discovery
We study the new task of class-incremental Novel Class Discovery (class-...
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07/11/2022
Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation
In this paper, we consider the problem of domain generalization in seman...
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04/06/2022
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation
In this paper, we study the task of synthetic-to-real domain generalized...
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03/05/2022
Federated and Generalized Person Re-identification through Domain and Feature Hallucinating
In this paper, we study the problem of federated domain generalization (...
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03/03/2022
Cross-Modality Earth Mover's Distance for Visible Thermal Person Re-Identification
Visible thermal person re-identification (VT-ReID) suffers from the inte...
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12/03/2021
Novel Class Discovery in Semantic Segmentation
We introduce a new setting of Novel Class Discovery in Semantic Segmenta...
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12/02/2021
3D-Aware Semantic-Guided Generative Model for Human Synthesis
Generative Neural Radiance Field (GNeRF) models, which extract implicit ...
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11/19/2021
Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation
In autonomous driving, learning a segmentation model that can adapt to v...
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08/19/2021
A Unified Objective for Novel Class Discovery
In this paper, we study the problem of Novel Class Discovery (NCD). NCD ...
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06/20/2021
Neighborhood Contrastive Learning for Novel Class Discovery
In this paper, we address Novel Class Discovery (NCD), the task of unvei...
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06/07/2021
Source-Free Open Compound Domain Adaptation in Semantic Segmentation
In this work, we introduce a new concept, named source-free open compoun...
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05/28/2021
Transformer-Based Source-Free Domain Adaptation
In this paper, we study the task of source-free domain adaptation (SFDA)...
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04/01/2021
Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation
In this paper we address multi-target domain adaptation (MTDA), where gi...
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03/08/2021
Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification
This paper considers the problem of unsupervised person re-identificatio...
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12/01/2020
Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification
Recent advances in person re-identification (ReID) obtain impressive acc...
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04/12/2020
OpenMix: Reviving Known Knowledge for Discovering Novel Visual Categories in An Open World
In this paper, we tackle the problem of discovering new classes in unlab...
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12/03/2019
Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification
Person re-identification (re-ID), is a challenging task due to the high ...
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08/01/2019
Learning to Adapt Invariance in Memory for Person Re-identification
This work considers the problem of unsupervised domain adaptation in per...
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04/03/2019
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
This paper considers the domain adaptive person re-identification (re-ID...
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11/05/2018
Leveraging Virtual and Real Person for Unsupervised Person Re-identification
Person re-identification (re-ID) is a challenging problem especially whe...
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01/30/2018
Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification
This paper considers the task of thorax disease classification on chest ...
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11/28/2017
Camera Style Adaptation for Person Re-identification
Being a cross-camera retrieval task, person re-identification suffers fr...
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01/29/2017
Re-ranking Person Re-identification with k-reciprocal Encoding
When considering person re-identification (re-ID) as a retrieval process...
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06/03/2015
