Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Yang, Shuzhou"'
Single image-to-3D generation is pivotal for crafting controllable 3D assets. Given its under-constrained nature, we attempt to leverage 3D geometric priors from a novel view diffusion model and 2D appearance priors from an image generation model to
Externí odkaz:
http://arxiv.org/abs/2405.20669
3D Gaussian Splatting (3DGS) has marked a significant breakthrough in the realm of 3D scene reconstruction and novel view synthesis. However, 3DGS, much like its predecessor Neural Radiance Fields (NeRF), struggles to accurately model physical reflec
Externí odkaz:
http://arxiv.org/abs/2404.01168
Universal image restoration is a practical and potential computer vision task for real-world applications. The main challenge of this task is handling the different degradation distributions at once. Existing methods mainly utilize task-specific cond
Externí odkaz:
http://arxiv.org/abs/2403.11157
Autor:
Li, Zihan, Zheng, Yuan, Shan, Dandan, Yang, Shuzhou, Li, Qingde, Wang, Beizhan, Zhang, Yuanting, Hong, Qingqi, Shen, Dinggang
Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional la
Externí odkaz:
http://arxiv.org/abs/2402.02029
Diffusion models have revolutionized text-driven video editing. However, applying these methods to real-world editing encounters two significant challenges: (1) the rapid increase in GPU memory demand as the number of frames grows, and (2) the inter-
Externí odkaz:
http://arxiv.org/abs/2312.08882
Existing unsupervised low-light image enhancement methods lack enough effectiveness and generalization in practical applications. We suppose this is because of the absence of explicit supervision and the inherent gap between real-world scenarios and
Externí odkaz:
http://arxiv.org/abs/2308.09279
Rain streaks significantly decrease the visibility of captured images and are also a stumbling block that restricts the performance of subsequent computer vision applications. The existing deep learning-based image deraining methods employ manually c
Externí odkaz:
http://arxiv.org/abs/2305.18092
The following three factors restrict the application of existing low-light image enhancement methods: unpredictable brightness degradation and noise, inherent gap between metric-favorable and visual-friendly versions, and the limited paired training
Externí odkaz:
http://arxiv.org/abs/2303.11722
Neural radiance fields (NeRF) bring a new wave for 3D interactive experiences. However, as an important part of the immersive experiences, the defocus effects have not been fully explored within NeRF. Some recent NeRF-based methods generate 3D defocu
Externí odkaz:
http://arxiv.org/abs/2203.05189
Publikováno v:
In Pattern Recognition February 2025 158
