CREEK 发表于 2025-3-26 22:42:36

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富饶 发表于 2025-3-27 03:54:35

Spatial-Adaptive Network for Single Image Denoising, By conducting noise removal from coarse to fine, a high-quality noise-free image is obtained. We apply our method to both synthetic and real noisy image datasets. The experimental results demonstrate that our method outperforms the state-of-the-art denoising methods both quantitatively and visually.

GOAD 发表于 2025-3-27 06:36:28

Physics-Based Feature Dehazing Networks,The residual learning is applied to increase the accuracy and ease the training of deep neural networks. We analyze the effectiveness of the proposed network and demonstrate that it can effectively dehaze images with favorable performance against state-of-the-art methods.

自传 发表于 2025-3-27 13:26:48

Learning Surrogates via Deep Embedding,t distance metric and achieves up to . relative improvement in the total edit distance. In the detection task, the surrogate approximates the intersection over union metric for rotated bounding boxes and yields up to . relative improvement in the . score.

oracle 发表于 2025-3-27 14:57:37

High-Quality Single-Model Deep Video Compression with Frame-Conv3D and Multi-frame Differential Modmance. A dropout scheme combined with the differential modulator is proposed to enable bit rate optimization within a single model. Experimental results show that the proposed approach outperforms the H.264 and H.265 codecs in the region of low bit rate. Compared with recent DL-based methods, our model also achieves competitive performance.

PANEL 发表于 2025-3-27 18:04:53

Self-Paced Deep Regression Forests with Consideration on Underrepresented Examples,ctive: fairness. This paradigm is fundamental and could be easily combined with a variety of deep discriminative models (DDMs). Extensive experiments on two computer vision tasks, i.e., facial age estimation and head pose estimation, demonstrate the efficacy of SPUDRFs, where state-of-the-art performances are achieved.

连锁,连串 发表于 2025-3-27 22:11:57

Conference proceedings 2020n, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic..The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with top

演绎 发表于 2025-3-28 05:54:51

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得罪人 发表于 2025-3-28 08:56:03

Trading Mechanisms on Financial Markets,mportant past frames and construct a sparse graph to apply in the GCN framework, well-capturing the structure information in action sequences. Extensive experimental results demonstrate the superiority of our method on two standard human action datasets compared with existing methods.

虚度 发表于 2025-3-28 12:54:44

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查看完整版本: Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur