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

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書(shū)目名稱(chēng)Computer Vision – ECCV 2024影響因子(影響力)




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書(shū)目名稱(chēng)Computer Vision – ECCV 2024讀者反饋




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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 generali

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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

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,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 train

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,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

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