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Related papers: Magic3D: High-Resolution Text-to-3D Content Creati…

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3D generation has raised great attention in recent years. With the success of text-to-image diffusion models, the 2D-lifting technique becomes a promising route to controllable 3D generation. However, these methods tend to present…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Tianyu Huang , Yihan Zeng , Zhilu Zhang , Wan Xu , Hang Xu , Songcen Xu , Rynson W. H. Lau , Wangmeng Zuo

Neural radiance fields (NeRFs) enable novel view synthesis with unprecedented visual quality. However, to render photorealistic images, NeRFs require hundreds of deep multilayer perceptron (MLP) evaluations - for each pixel. This is…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Ziyu Wan , Christian Richardt , Aljaž Božič , Chao Li , Vijay Rengarajan , Seonghyeon Nam , Xiaoyu Xiang , Tuotuo Li , Bo Zhu , Rakesh Ranjan , Jing Liao

Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative applications like visual effects in filmmaking. Previous…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Songlin Yang , Yushi Lan , Honghua Chen , Xingang Pan

While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a significant challenge due to the complexities of multi-view consistency and spatial control.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jinxin Ai , Matthias Nießner , Ziya Erkoç

With dense inputs, Neural Radiance Fields (NeRF) is able to render photo-realistic novel views under static conditions. Although the synthesis quality is excellent, existing NeRF-based methods fail to obtain moderate three-dimensional (3D)…

Computer Vision and Pattern Recognition · Computer Science 2024-02-21 Shu Chen , Junyao Li , Yang Zhang , Beiji Zou

Neural Radiance Field (NeRF) has broken new ground in the novel view synthesis due to its simple concept and state-of-the-art quality. However, it suffers from severe performance degradation unless trained with a dense set of images with…

Computer Vision and Pattern Recognition · Computer Science 2023-04-13 Seunghyeon Seo , Donghoon Han , Yeonjin Chang , Nojun Kwak

Recent work on Neural Radiance Fields (NeRF) exploits multi-view 3D consistency, achieving impressive results in 3D scene modeling and high-fidelity novel-view synthesis. However, there are limitations. First, existing methods assume enough…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Mengfei Li , Ming Lu , Xiaofang Li , Shanghang Zhang

The ability to create high-quality 3D faces from a single image has become increasingly important with wide applications in video conferencing, AR/VR, and advanced video editing in movie industries. In this paper, we propose Face Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Hao Zhang , Yanbo Xu , Tianyuan Dai , Yu-Wing Tai , Chi-Keung Tang

While dynamic Neural Radiance Fields (NeRF) have shown success in high-fidelity 3D modeling of talking portraits, the slow training and inference speed severely obstruct their potential usage. In this paper, we propose an efficient…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Jiaxiang Tang , Kaisiyuan Wang , Hang Zhou , Xiaokang Chen , Dongliang He , Tianshu Hu , Jingtuo Liu , Gang Zeng , Jingdong Wang

Neural Radiance Fields (NeRF) have demonstrated remarkable performance in novel view synthesis. However, there is much improvement room on restoring 3D scenes based on NeRF from corrupted images, which are common in natural scene captures…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Xianliang Huang , Zhizhou Zhong , Shuhang Chen , Yi Xu , Juhong Guan , Shuigeng Zhou

We propose StyleNeRF, a 3D-aware generative model for photo-realistic high-resolution image synthesis with high multi-view consistency, which can be trained on unstructured 2D images. Existing approaches either cannot synthesize…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Jiatao Gu , Lingjie Liu , Peng Wang , Christian Theobalt

Neural rendering has garnered substantial attention owing to its capacity for creating realistic 3D scenes. However, its applicability to extensive scenes remains challenging, with limitations in effectiveness. In this work, we propose the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Zhihao Jia , Bing Wang , Changhao Chen

The emergence of Neural Radiance Fields (NeRF) has greatly impacted 3D scene modeling and novel-view synthesis. As a kind of visual media for 3D scene representation, compression with high rate-distortion performance is an eternal target.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Sicheng Li , Hao Li , Yiyi Liao , Lu Yu

We introduce InFusionSurf, an innovative enhancement for neural radiance field (NeRF) frameworks in 3D surface reconstruction using RGB-D video frames. Building upon previous methods that have employed feature encoding to improve…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Seunghwan Lee , Gwanmo Park , Hyewon Son , Jiwon Ryu , Han Joo Chae

In the realm of text-to-3D generation, utilizing 2D diffusion models through score distillation sampling (SDS) frequently leads to issues such as blurred appearances and multi-faced geometry, primarily due to the intrinsically noisy nature…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Pengsheng Guo , Hans Hao , Adam Caccavale , Zhongzheng Ren , Edward Zhang , Qi Shan , Aditya Sankar , Alexander G. Schwing , Alex Colburn , Fangchang Ma

Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance from pre-trained diffusion models. An apparent drawback is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Yiji Cheng , Fei Yin , Xiaoke Huang , Xintong Yu , Jiaxiang Liu , Shikun Feng , Yujiu Yang , Yansong Tang

Image fusion seeks to seamlessly integrate foreground objects with background scenes, producing realistic and harmonious fused images. Unlike existing methods that directly insert objects into the background, adaptive and interactive fusion…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Junjia Huang , Pengxiang Yan , Jiyang Liu , Jie Wu , Zhao Wang , Yitong Wang , Liang Lin , Guanbin Li

We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with the given text descriptions. Due to a novel and efficient 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Daquan Zhou , Weimin Wang , Hanshu Yan , Weiwei Lv , Yizhe Zhu , Jiashi Feng

The neural radiance field (NeRF) achieved remarkable success in modeling 3D scenes and synthesizing high-fidelity novel views. However, existing NeRF-based methods focus more on the make full use of the image resolution to generate novel…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Yuqi Han , Tao Yu , Xiaohang Yu , Yuwang Wang , Qionghai Dai

We present a method to synthesize novel views from a single $360^\circ$ panorama image based on the neural radiance field (NeRF). Prior studies in a similar setting rely on the neighborhood interpolation capability of multi-layer…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Shreyas Kulkarni , Peng Yin , Sebastian Scherer