Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts

2023-02-26T10:27:05+00:00

Improving model's generalizability against domain shifts is crucial, especially for safety-critical applications such as autonomous driving. Real-world domain styles can vary substantially due to [...]

Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts2023-02-26T10:27:05+00:00

Pix2NeRF: Unsupervised Conditional p-GAN for Single Image to Neural Radiance Fields Translation

2022-12-05T16:03:07+00:00

Pix2NeRF: Unsupervised Conditional p-GAN for Single Image to Neural Radiance Fields Translation Shengqu Cai, Anton Obukhov, Dengxin Dai, Luc Van Gool We propose [...]

Pix2NeRF: Unsupervised Conditional p-GAN for Single Image to Neural Radiance Fields Translation2022-12-05T16:03:07+00:00

CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning

2022-12-05T10:43:03+00:00

Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning Yue Fan, Dengxin Dai, Anna Kukleva, Bernt Schiele Standard semi-supervised learning (SSL) using class-balanced [...]

CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning2022-12-05T10:43:03+00:00

End-to-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization

2022-10-24T20:03:06+00:00

End-to-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization Niclas Vödisch, Ozan Unal, Ke Li, Luc Van Gool, and Dengxin Dai [...]

End-to-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization2022-10-24T20:03:06+00:00
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