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Rendering photo-realistic novel-view images of complex scenes has been a long-standing challenge in computer graphics. In recent years, great research progress has been made on enhancing rendering quality and accelerating rendering speed in…

Graphics · Computer Science 2024-02-21 Tiansong Zhou , Yebin Liu , Xuangeng Chu , Chengkun Cao , Changyin Zhou , Fei Yu , Yu Li

In this paper, we propose VistaDream a novel framework to reconstruct a 3D scene from a single-view image. Recent diffusion models enable generating high-quality novel-view images from a single-view input image. Most existing methods only…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiping Wang , Yuan Liu , Ziwei Liu , Wenping Wang , Zhen Dong , Bisheng Yang

Humans can infer 3D structure from 2D images of an object based on past experience and improve their 3D understanding as they see more images. Inspired by this behavior, we introduce SAP3D, a system for 3D reconstruction and novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Xinyang Han , Zelin Gao , Angjoo Kanazawa , Shubham Goel , Yossi Gandelsman

Image compression methods are usually optimized isolatedly for human perception or machine analysis tasks. We reveal fundamental commonalities between these objectives: preserving accurate semantic information is paramount, as it directly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Ruoyu Feng , Yunpeng Qi , Jinming Liu , Yixin Gao , Xin Li , Xin Jin , Zhibo Chen

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

Text-driven person image generation is an emerging and challenging task in cross-modality image generation. Controllable person image generation promotes a wide range of applications such as digital human interaction and virtual try-on.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-14 Kaiduo Zhang , Muyi Sun , Jianxin Sun , Binghao Zhao , Kunbo Zhang , Zhenan Sun , Tieniu Tan

In this work, we introduce \textbf{Wonder3D++}, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Yuxiao Yang , Xiao-Xiao Long , Zhiyang Dou , Cheng Lin , Yuan Liu , Qingsong Yan , Yuexin Ma , Haoqian Wang , Zhiqiang Wu , Wei Yin

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model generation are restricted to low resolutions with suboptimal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Yihang Luo , Shangchen Zhou , Yushi Lan , Xingang Pan , Chen Change Loy

Recent breakthroughs in video generation, powered by large-scale datasets and diffusion techniques, have shown that video diffusion models can function as implicit 4D novel view synthesizers. Nevertheless, current methods primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yihao Zhi , Chenghong Li , Hongjie Liao , Xihe Yang , Zhengwentai Sun , Jiahao Chang , Xiaodong Cun , Wensen Feng , Xiaoguang Han

Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand in stark contrast to the compact, structured, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuan Li , Cheng Lin , Yuan Liu , Xiaoxiao Long , Chenxu Zhang , Ningna Wang , Xin Li , Wenping Wang , Xiaohu Guo

Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving the consistency of objects and background without changing…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Liyao Jiang , Negar Hassanpour , Mohammad Salameh , Mohammadreza Samadi , Jiao He , Fengyu Sun , Di Niu

Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jiatao Gu , Qingzhe Gao , Shuangfei Zhai , Baoquan Chen , Lingjie Liu , Josh Susskind

Recent advances in diffusion models have enabled 3D generation from a single image. However, current methods often produce suboptimal results for novel views, with blurred textures and deviations from the reference image, limiting their…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Wangbo Yu , Li Yuan , Yan-Pei Cao , Xiangjun Gao , Xiaoyu Li , Wenbo Hu , Long Quan , Ying Shan , Yonghong Tian

Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Haoran Wei , Wencheng Han , Xingping Dong , Jianbing Shen

Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered from novel camera views, existing single image to 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Sarosij Bose , Arindam Dutta , Sayak Nag , Junge Zhang , Jiachen Li , Konstantinos Karydis , Amit K. Roy Chowdhury

Despite significant advances in large-scale text-to-image models, achieving hyper-realistic human image generation remains a desirable yet unsolved task. Existing models like Stable Diffusion and DALL-E 2 tend to generate human images with…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Xian Liu , Jian Ren , Aliaksandr Siarohin , Ivan Skorokhodov , Yanyu Li , Dahua Lin , Xihui Liu , Ziwei Liu , Sergey Tulyakov

Despite remarkable progress having been made on the problem of 3D human pose and shape estimation (HPS), current state-of-the-art methods rely heavily on either confined indoor mocap datasets or datasets generated by a rendering engine…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Yongtao Ge , Wenjia Wang , Yongfan Chen , Fanzhou Wang , Lei Yang , Hao Chen , Chunhua Shen

In recent years, diffusion models have revolutionized visual generation, outperforming traditional frameworks like Generative Adversarial Networks (GANs). However, generating images of humans with realistic semantic parts, such as hands and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Benzhi Wang , Jingkai Zhou , Jingqi Bai , Yang Yang , Weihua Chen , Fan Wang , Zhen Lei

We present a novel framework for high-fidelity novel view synthesis (NVS) from sparse images, addressing key limitations in recent feed-forward 3D Gaussian Splatting (3DGS) methods built on Vision Transformer (ViT) backbones. While…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yitong Dong , Qi Zhang , Minchao Jiang , Zhiqiang Wu , Qingnan Fan , Ying Feng , Huaqi Zhang , Hujun Bao , Guofeng Zhang