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Titlebook: Computer Vision – ECCV 2024; 18th European Confer Aleš Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

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Hanna Zieschang,Dietmar Bräunigs. Particularly noteworthy is the challenge posed by catastrophic overfitting (CO) in this field. Although existing FAT approaches have made strides in mitigating CO, the ascent of adversarial robustness occurs with a non-negligible decline in classification accuracy on clean samples. To tackle this
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https://doi.org/10.1007/978-3-658-37883-7ng solely on text prompts often results in ambiguous frame composition due to spatial uncertainty. The research community thus leverages the . structure signals, ., per-frame depth/edge sequences to enhance controllability, whose collection accordingly increases the burden of inference. In this work
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Conference proceedings 2025orcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation... .
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0302-9743 n; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation... .978-3-031-72945-4978-3-031-72946-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Das Altern im Spiegelbild der Stammzellenus activities of multiple users. We exploit WiMANS to benchmark the performance of state-of-the-art WiFi-based human sensing models and video-based models, posing new challenges and opportunities for future work. We believe WiMANS can push the boundaries of current studies and catalyze the research on WiFi-based multi-user sensing.
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