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Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse weather conditions, sensor failure, and noise contamination, is desirable for safety-critical applications.
The pascal visual object classes (voc) challenge
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Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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Simipu: Simple 2d image and 3d point cloud unsupervised pre-training for spatial-aware visual representations
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Christoph Kamann and Carsten Rother · 2020
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Defeat-net: General monocular depth via simultaneous unsupervised representation learning
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D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry
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