发源
发表于 2025-3-26 22:35:26
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THE
发表于 2025-3-27 01:11:27
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Affable
发表于 2025-3-27 08:24:48
,Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder,l metric Fréchet Denoised Distance (FDD). We experimentally test our FDD, FID and other state-of-the-art metrics on multiple datasets, .., BIKED, Seeing3DChairs, FFHQ and ImageNet. Our FDD can effectively detect implausible structures and is more consistent with structural inspections by human experts. Our source code is publicly available at ..
发电机
发表于 2025-3-27 13:31:39
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OREX
发表于 2025-3-27 17:03:40
Optimization-Based Uncertainty Attribution Via Learning Informative Perturbations,out manually tuning the perturbation parameters; and a novel application of Gumbel-sigmoid reparameterization for efficiently learning Bernoulli-distributed binary masks under continuous optimization. Our experiments on problematic region detection and faithfulness tests demonstrate our method’s superiority over state-of-the-art UA methods.
intrude
发表于 2025-3-27 18:35:52
,Context-Aware Action Recognition: Introducing a Comprehensive Dataset for Behavior Contrast,lso extends to everyday situations like basketball, underscoring the task’s broad relevance. By evaluating leading techniques on this dataset, we aim to unearth valuable insights, pushing the boundaries of action understanding in both industrial and everyday contexts.
GROSS
发表于 2025-3-27 22:51:20
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Jejune
发表于 2025-3-28 05:03:29
https://doi.org/10.1007/978-3-476-05116-5rops in the image and camera intrinsics. Experiments on three popular 3D-from-a-single-image benchmarks: depth prediction on NYU, 3D object detection on KITTI & nuScenes, and predicting 3D shapes of articulated objects on ARCTIC, show the benefits of KPE.
小故事
发表于 2025-3-28 07:53:01
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heterogeneous
发表于 2025-3-28 11:35:40
Mark Docherty,Andrew Carson,Matthew Ward on 11 benchmark downstream classification tasks with 4 popular pre-trained models. Our method is . better than the deep features without SeA on average. Moreover, compared to the expensive fine-tuning that is expected to give good performance, SeA shows a comparable performance on 6 out of 11 tasks