Preprints (🚩: corresponding authors; 🥇: co-first authors)
Masked Relation Learning for DeepFake Detection.
Abstract:
submitted to IEEE Transactions on Information Forensics and Security (TIFS), under review, 2022.
ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation.
Abstract:
submitted to IEEE Transactions on Image Processing (TIP), under review, 2022. [Paper] [Code]
Source Data-Free Cross-Domain Semantic Segmentation: Align, Teach and Propagate.
Abstract:
submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), under review, 2022. [Paper]
Color-Unrelated Head-Shoulder Networks for Fine-Grained Person Re-identification.
Abstract:
submitted to ACM Transactions on Multimedia Computing, Communications, and Application (TOMM), major revision, 2022.
Reciprocal Normalization for Domain Adaptation.
Abstract:
submitted to Pattern Recognition (PR), major revision, 2022. [Paper] [Code]
Towards Fair Domain Adaptation with xxx.
Abstract:
submitted to Proc. xxx, under review, 2023.
xxx for Deepfake Video Detection with Transformers.
Abstract:
submitted to Proc. xxx, under review, 2023.
xxx for Efficient Cross-Domain Semantic Segmentation.
Abstract:
submitted to Proc. xxx, under review, 2023.
xxx for Fingerprinting Deep Neural Networks.
Abstract:
submitted to Proc. xxx, under review, 2022.
Towards xxx in Heterogeneous Federated Learning.
Abstract:
submitted to Proc. xxx, under review, 2022.
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization.
Abstract:
Arxiv technical report, 2022. [Paper] [Link]
UMAD: Universal Model Adaptation under Domain and Category Shift.
Abstract:
Arxiv technical report, 2021. [Paper] [Link]
Semi-Supervised Domain Generalizable Person Re-Identification.
Abstract:
Arxiv technical report, 2021. [Paper] [Link]
On Evolving Attention Towards Domain Adaptation.
Abstract:
Arxiv technical report, 2021. [Paper] [Link]
Robust Localized Multi-view Subspace Clustering.
Abstract:
Arxiv technical report, 2017. [Paper] [Link] Publications [2022] [2021] [2020] [2019] [2018] [2017] [2016] [2015]
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer.
Abstract:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), In Press [Paper] [Appendix] [Link] [Code]
Learning Feature Recovery Transformer for Occluded Person Re-identification.
Abstract:
IEEE Transactions on Image Processing (TIP), 2022. [Paper] [Link]
Heterogeneous Face Recognition via Face Synthesis with Identity-Attribute Disentanglement.
Abstract:
IEEE Transactions on Information Forensics and Security (TIFS), 2022 [Paper] [Link]
DINE: Domain Adaptation from Single and Multiple Black-box Predictors.
Abstract:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (Oral) [Paper] [Link] [Code] [Slides]
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning.
Abstract:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 [Paper] [Link] [Code]
META: Mimicking Embedding via oThers' Aggregation for Generalizable Person Re-identification.
Abstract:
European Conference on Computer Vision (ECCV), 2022. [Paper] [Link]
Diagnostic Classification for Human Autism and Obsessive-Compulsive Disorder Based on Machine Learning From a Primate Genetic Model.
Abstract:
American Journal of Psychiatry (AJP), 2021 [Paper] [Link]
Adversarial Domain Adaptation with Prototype-Based Normalized Output Conditioner.
Abstract:
IEEE Transactions on Image Processing (TIP), 2021 [Paper] [Link] [Code]
Deep Semantic Reconstruction Hashing for Similarity Retrieval.
Abstract:
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2021 [Paper] [Link]
Domain Adaptation with Auxiliary Target Domain-Oriented Classifier.
Abstract:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 [Paper] [Link] [Code] [Slides]
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data.
Abstract:
Annual Conference on Neural Information Processing Systems (NeurIPS), 2021 [Paper] [Link]
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning.
Abstract:
Annual Conference on Neural Information Processing Systems (NeurIPS), 2021 [Paper] [Link] [Code] [Slides]
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation.
Abstract:
International Conference on Machine Learning (ICML), 2020 [Paper] [Link] [Code] [Slides]
A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation.
Abstract:
European Conference on Computer Vision (ECCV), 2020 [Paper] [Link] [Code] [Slides]
Aggregating Randomized Clustering-Promoting Invariant Projections for Domain Adaptation.
Abstract:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 [Paper] [Appendix] [Link] [Code] [Office-Home-ResNet-features (password: rb13)]
Local Semantic-aware Deep Hashing with Hamming-isometric Quantization.
Abstract:
IEEE Transactions on Image Processing (TIP), 2019 [Paper] [Link]
Exploring Uncertainty in Pseudo-label Guided Unsupervised Domain Adaptation.
Abstract:
Pattern Recognition (PR), 2019 [Paper] [Link] [Code]
Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation.
Abstract:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [Paper] [Link] [Code]
Deep Spatial Feature Reconstruction for Partial Person Re-Identification: Alignment-Free Approach.
Abstract:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [Paper] [Link] [Code]
X-GACMN: An X-Shaped Generative Adversarial Cross-Modal Network with Hypersphere Embedding.
Abstract:
Asian Conference on Computer Vision (ACCV), 2018 [Paper] [Link]
Learning Discriminative Geodesic Flow Kernel for Unsupervised Domain Adaptation.
Abstract:
IEEE International Conference on Multimedia and Expo (ICME), 2018 (Oral) [Paper] [Link] [Slides]
Nonlinear Discrete Cross-Modal Hashing for Visual-Textual Data.
Abstract:
IEEE MultiMedia (IEEE MM), 2017 [Paper] [Link] [Code]
Self-Paced Learning: an Implicit Regularization Perspective.
Abstract:
AAAI Conference on Artificial Intelligence (AAAI), 2017 (Oral) [Paper] [Link]
Self-Paced Cross-Modal Subspace Matching.
Abstract:
International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2016 (Oral) [Paper] [Link] [Slides] [Code] [Dataset]
Group-Invariant Cross-Modal Subspace Learning.
Abstract:
International Joint Conference on Artificial Intelligence (IJCAI), 2016 (Oral) [Paper] [Link] [Code] [Slides]
Frustratingly Easy Cross-Modal Hashing.
Abstract:
Annual ACM Conference on Multimedia Conference (ACM MM), 2016 [Paper] [Link] [Code] [Dataset]
Discrete Cross-Modal Hashing for Efficient Multimedia Retrieval.
Abstract:
IEEE International Symposium on Multimedia (ISM), Best Paper Candidate, 2016 [Paper] [Link]
Code Consistent Hashing Based on Information-Theoretic Criterion.
Abstract:
IEEE Transactions on Big Data (TBD), 2015 [Paper] [Link]
Two-Step Greedy Subspace Clustering.
Abstract:
Advances in Multimedia Information Processing (PCM), 2015 (Oral) [Paper] [Link]
Principal Affinity Based Cross-Modal Retrieval.
Abstract:
IAPR Asian Conference on Pattern Recognition (ACPR), 2015 [Paper] [Link] [Code] |