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Novel view synthesis requires strong 3D geometric consistency and the ability to generate visually coherent images across diverse viewpoints. While recent camera-controlled video diffusion models show promising results, they often suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Minjun Kang , Inkyu Shin , Taeyeop Lee , Myungchul Kim , In So Kweon , Kuk-Jin Yoon

Novel View Synthesis (NVS) for street scenes play a critical role in the autonomous driving simulation. The current mainstream technique to achieve it is neural rendering, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Zhongrui Yu , Haoran Wang , Jinze Yang , Hanzhang Wang , Zeke Xie , Yunfeng Cai , Jiale Cao , Zhong Ji , Mingming Sun

In this paper, we present an approach for monocular open-set novel view synthesis (NVS) that leverages object skeletons to guide the underlying diffusion model. Building upon a baseline that utilizes a pre-trained 2D image generator, our…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Aron Fóthi , Bence Fazekas , Natabara Máté Gyöngyössy , Kristian Fenech

Novel-view synthesis aims to generate novel views of a scene from multiple input images or videos, and recent advancements like 3D Gaussian splatting (3DGS) have achieved notable success in producing photorealistic renderings with efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xi Liu , Chaoyi Zhou , Siyu Huang

Video generation models have progressed tremendously through large latent diffusion transformers trained with rectified flow techniques. Yet these models still struggle with geometric inconsistencies, unstable motion, and visual artifacts…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Orest Kupyn , Fabian Manhardt , Federico Tombari , Christian Rupprecht

Diffusion models offer unprecedented image generation power given just a text prompt. While emerging approaches for controlling diffusion models have enabled users to specify the desired spatial layouts of the generated content, they cannot…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Yunxiang Zhang , Nan Wu , Connor Z. Lin , Gordon Wetzstein , Qi Sun

In this paper, we present a diffusion model-based framework for animating people from a single image for a given target 3D motion sequence. Our approach has two core components: a) learning priors about invisible parts of the human body and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Boyi Li , Junming Chen , Jathushan Rajasegaran , Yossi Gandelsman , Alexei A. Efros , Jitendra Malik

High resolution panoramic video content is paramount for immersive experiences in Virtual Reality, but is non-trivial to collect as it requires specialized equipment and intricate camera setups. In this work, we introduce VideoPanda, a…

Video generation has drawn significant interest recently, pushing the development of large-scale models capable of producing realistic videos with coherent motion. Due to memory constraints, these models typically generate short video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Idan Kligvasser , Regev Cohen , George Leifman , Ehud Rivlin , Michael Elad

A recent strand of work in view synthesis uses deep learning to generate multiplane images (a camera-centric, layered 3D representation) given two or more input images at known viewpoints. We apply this representation to single-view view…

Computer Vision and Pattern Recognition · Computer Science 2020-04-24 Richard Tucker , Noah Snavely

We present Stable Video 4D (SV4D), a latent video diffusion model for multi-frame and multi-view consistent dynamic 3D content generation. Unlike previous methods that rely on separately trained generative models for video generation and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Yiming Xie , Chun-Han Yao , Vikram Voleti , Huaizu Jiang , Varun Jampani

3D Gaussian Splatting has recently emerged as a powerful tool for fast and accurate novel-view synthesis from a set of posed input images. However, like most novel-view synthesis approaches, it relies on accurate camera pose information,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Christian Schmidt , Jens Piekenbrinck , Bastian Leibe

Currently almost all state-of-the-art novel view synthesis and reconstruction models rely on calibrated cameras or additional geometric priors for training. These prerequisites significantly limit their applicability to massive uncalibrated…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Ruoyu Wang , Yi Ma , Shenghua Gao

Photo-realistic re-rendering of a human from a single image with explicit control over body pose, shape and appearance enables a wide range of applications, such as human appearance transfer, virtual try-on, motion imitation, and novel view…

Computer Vision and Pattern Recognition · Computer Science 2021-02-23 Kripasindhu Sarkar , Vladislav Golyanik , Lingjie Liu , Christian Theobalt

The field of novel view synthesis has made significant strides thanks to the development of radiance field methods. However, most radiance field techniques are far better at novel view interpolation than novel view extrapolation where the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Kunhao Liu , Ling Shao , Shijian Lu

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

In this work, we rethink the approach to video super-resolution by introducing a method based on the Diffusion Posterior Sampling framework, combined with an unconditional video diffusion transformer operating in latent space. The video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Zhihao Zhan , Wang Pang , Xiang Zhu , Yechao Bai

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate new samples, has been shown to handle complex data…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Zhengxiong Luo , Dayou Chen , Yingya Zhang , Yan Huang , Liang Wang , Yujun Shen , Deli Zhao , Jingren Zhou , Tieniu Tan

Novel View Synthesis (NVS) aims to generate unseen views of a 3D object given a limited number of known views. Existing methods often struggle to synthesize plausible views for unobserved regions, particularly under single-view input, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Jinglin Liang , Zijian Zhou , Rui Huang , Shuangping Huang , Yichen Gong