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07/23/2023
Improving Out-of-Distribution Robustness of Classifiers via Generative Interpolation
Deep neural networks achieve superior performance for learning from inde...
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06/15/2023
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
Modern machine learning models deployed in the wild can encounter both c...
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09/06/2021
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection
We present a flexible and high-performance framework, named Pyramid R-CN...
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09/06/2021
Voxel Transformer for 3D Object Detection
We present Voxel Transformer (VoTr), a novel and effective voxel-based T...
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09/05/2021
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization
Recent advances on Out-of-Distribution (OoD) generalization reveal the r...
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06/07/2021
OoD-Bench: Benchmarking and Understanding Out-of-Distribution Generalization Datasets and Algorithms
Deep learning has achieved tremendous success with independent and ident...
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05/20/2021
Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification
Labeled crowd scene images are expensive and scarce. To significantly re...
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04/28/2021
Motion-guided Non-local Spatial-Temporal Network for Video Crowd Counting
We study video crowd counting, which is to estimate the number of object...
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12/31/2020
CNN-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal
Single image crowd counting is a challenging computer vision problem wit...
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12/17/2020
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation
While deep learning demonstrates its strong ability to handle independen...
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09/09/2019