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08/24/2023
Towards Realistic Unsupervised Fine-tuning with CLIP
The emergence of vision-language models (VLMs), such as CLIP, has spurre...
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08/16/2023
DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory
Controllable video generation has gained significant attention in recent...
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08/11/2023
Test-Time Adaptation for Backdoor Defense
Deep neural networks have played a crucial part in many critical domains...
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07/18/2023
Rumor Detection with Diverse Counterfactual Evidence
The growth in social media has exacerbated the threat of fake news to in...
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07/14/2023
TALL: Thumbnail Layout for Deepfake Video Detection
The growing threats of deepfakes to society and cybersecurity have raise...
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07/14/2023
PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation
Unsupervised domain adaptation (UDA) has witnessed remarkable advancemen...
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07/14/2023
Improving Zero-Shot Generalization for CLIP with Synthesized Prompts
With the growing interest in pretrained vision-language models like CLIP...
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07/06/2023
Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification
Test-time adaptation (TTA) is a technique aimed at enhancing the general...
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05/31/2023
Multi-Epoch Learning for Deep Click-Through Rate Prediction Models
The one-epoch overfitting phenomenon has been widely observed in industr...
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03/27/2023
A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts
Machine learning methods strive to acquire a robust model during trainin...
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03/27/2023
Mind the Label Shift of Augmentation-based Graph OOD Generalization
Out-of-distribution (OOD) generalization is an important issue for Graph...
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03/23/2023
Improving Generalization with Domain Convex Game
Domain generalization (DG) tends to alleviate the poor generalization ca...
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03/22/2023
AUTO: Adaptive Outlier Optimization for Online Test-Time OOD Detection
Out-of-distribution (OOD) detection is a crucial aspect of deploying mac...
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03/19/2023
AdaptGuard: Defending Against Universal Attacks for Model Adaptation
Model adaptation aims at solving the domain transfer problem under the c...
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03/17/2023
Exploiting Semantic Attributes for Transductive Zero-Shot Learning
Zero-shot learning (ZSL) aims to recognize unseen classes by generalizin...
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03/17/2023
MODIFY: Model-driven Face Stylization without Style Images
Existing face stylization methods always acquire the presence of the tar...
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02/09/2023
MAPS: A Noise-Robust Progressive Learning Approach for Source-Free Domain Adaptive Keypoint Detection
Existing cross-domain keypoint detection methods always require accessin...
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01/05/2023
Learning Feature Recovery Transformer for Occluded Person Re-identification
One major issue that challenges person re-identification (Re-ID) is the ...
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10/21/2022
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks
An off-the-shelf model as a commercial service could be stolen by model ...
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10/01/2022
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
Federated learning aims to train models collaboratively across different...
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07/20/2022
NUWA-Infinity: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis
In this paper, we present NUWA-Infinity, a generative model for infinite...
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06/19/2022
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization
This paper focuses on out-of-distribution generalization on graphs where...
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06/10/2022
Heterogeneous Face Recognition via Face Synthesis with Identity-Attribute Disentanglement
Heterogeneous Face Recognition (HFR) aims to match faces across differen...
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06/06/2022
A sentiment analysis model for car review texts based on adversarial training and whole word mask BERT
In the field of car evaluation, more and more netizens choose to express...
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06/01/2022
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder
Recently most successful image synthesis models are multi stage process ...
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05/29/2022
ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation
Unsupervised domain adaptation (UDA) aims to transfer knowledge from a l...
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04/25/2022
Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction
Rich user behavior information is of great importance for capturing and ...
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03/27/2022
Causality Inspired Representation Learning for Domain Generalization
Domain generalization (DG) is essentially an out-of-distribution problem...
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12/20/2021
Reciprocal Normalization for Domain Adaptation
Batch normalization (BN) is widely used in modern deep neural networks, ...
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12/16/2021
META: Mimicking Embedding via oThers' Aggregation for Generalizable Person Re-identification
Domain generalizable (DG) person re-identification (ReID) aims to test a...
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12/16/2021
UMAD: Universal Model Adaptation under Domain and Category Shift
Learning to reject unknown samples (not present in the source classes) i...
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12/09/2021
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning
Class Incremental Learning (CIL) aims at learning a multi-class classifi...
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12/08/2021
Pareto Domain Adaptation
Domain adaptation (DA) attempts to transfer the knowledge from a labeled...
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12/06/2021
Incentive Compatible Pareto Alignment for Multi-Source Large Graphs
In this paper, we focus on learning effective entity matching models ove...
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11/24/2021
NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion
This paper presents a unified multimodal pre-trained model called NÜWA t...
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08/19/2021
Fair and Consistent Federated Learning
Federated learning (FL) has gain growing interests for its capability of...
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08/18/2021
Learning to Collaborate
In this paper, we focus on effective learning over a collaborative resea...
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08/12/2021
Semantic Concentration for Domain Adaptation
Domain adaptation (DA) paves the way for label annotation and dataset bi...
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08/11/2021
Semi-Supervised Domain Generalizable Person Re-Identification
Existing person re-identification (re-id) methods are stuck when deploye...
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08/05/2021
Hybrid Reasoning Network for Video-based Commonsense Captioning
The task of video-based commonsense captioning aims to generate event-wi...
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06/22/2021
Give Me Your Trained Model: Domain Adaptive Semantic Segmentation without Source Data
Benefited from considerable pixel-level annotations collected from a spe...
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06/09/2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
A central challenge in training classification models in the real-world ...
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04/04/2021
Distill and Fine-tune: Effective Adaptation from a Black-box Source Model
To alleviate the burden of labeling, unsupervised domain adaptation (UDA...
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03/25/2021
On Evolving Attention Towards Domain Adaptation
Towards better unsupervised domain adaptation (UDA). Recently, researche...
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02/12/2021
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
Contrastive self-supervised learning (CSL) leverages unlabeled data to t...
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12/14/2020
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
Unsupervised domain adaptation (UDA) aims to transfer knowledge from a r...
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12/13/2020
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation
Unsupervised domain adaptation challenges the problem of transferring kn...
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11/01/2020
A Lane-Changing Prediction Method Based on Temporal Convolution Network
Lane-changing is an important driving behavior and unreasonable lane cha...
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10/15/2020
Reliable Evaluations for Natural Language Inference based on a Unified Cross-dataset Benchmark
Recent studies show that crowd-sourced Natural Language Inference (NLI) ...
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10/12/2020