Harding 发表于 2025-3-21 17:38:25
书目名称Computer Vision – ECCV 2024影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0242314<br><br> <br><br>书目名称Computer Vision – ECCV 2024读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0242314<br><br> <br><br>HEAVY 发表于 2025-3-22 00:16:44
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,OGNI-DC: Robust Depth Completion with Optimization-Guided Neural Iterations,el framework for depth completion. The key to our method is “.ptimization-.uided .eural .terations” (OGNI). It consists of a recurrent unit that refines a depth gradient field and a differentiable depth integrator that integrates the depth gradients into a depth map. OGNI-DC exhibits strong generaliEngaged 发表于 2025-3-22 15:41:06
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Beta-Tuned Timestep Diffusion Model,cent studies indicate that treating all distributions equally in diffusion model training is sub-optimal. In this paper, we conduct an in-depth theoretical analysis of the forward process of diffusion models. Our findings reveal that the distribution variations are non-uniform throughout the diffusi大火 发表于 2025-3-22 22:54:43
,POA: Pre-training Once for Models of All Sizes,gies train a single model of a certain size at one time. Nevertheless, various computation or storage constraints in real-world scenarios require substantial efforts to develop a series of models with different sizes to deploy. Thus, in this study, we propose a novel tri-branch self-supervised trainJacket 发表于 2025-3-23 03:16:21
,Taming Latent Diffusion Model for Neural Radiance Field Inpainting, editing a reconstructed NeRF with diffusion prior, they remain struggling to synthesize reasonable geometry in completely uncovered regions. One major reason is the high diversity of synthetic contents from the diffusion model, which hinders the radiance field from converging to a crisp and determi埋葬 发表于 2025-3-23 08:22:31
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