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The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unified model capable of handling various tasks within a single…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Shitao Xiao , Yueze Wang , Junjie Zhou , Huaying Yuan , Xingrun Xing , Ruiran Yan , Chaofan Li , Shuting Wang , Tiejun Huang , Zheng Liu

This paper proposes Instruct 4D-to-4D that achieves 4D awareness and spatial-temporal consistency for 2D diffusion models to generate high-quality instruction-guided dynamic scene editing results. Traditional applications of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Linzhan Mou , Jun-Kun Chen , Yu-Xiong Wang

This paper proposes ConsistDreamer - a novel framework that lifts 2D diffusion models with 3D awareness and 3D consistency, thus enabling high-fidelity instruction-guided scene editing. To overcome the fundamental limitation of missing 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Jun-Kun Chen , Samuel Rota Bulò , Norman Müller , Lorenzo Porzi , Peter Kontschieder , Yu-Xiong Wang

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

By harnessing the potent generative capabilities of pre-trained large video diffusion models, we propose NVS-Solver, a new novel view synthesis (NVS) paradigm that operates \textit{without} the need for training. NVS-Solver adaptively…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Meng You , Zhiyu Zhu , Hui Liu , Junhui Hou

Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current foundational models predominantly focus on processing images,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhiyu Tan , Hao Yang , Luozheng Qin , Jia Gong , Mengping Yang , Hao Li

Recent advances in diffusion models have achieved remarkable success in isolated computer vision tasks such as text-to-image generation, depth estimation, and optical flow. However, these models are often restricted by a…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Yilin Gao , Shuguang Dou , Junzhou Li , Zhiheng Yu , Yin Li , Dongsheng Jiang , Shugong Xu

Utilizing pre-trained 2D large-scale generative models, recent works are capable of generating high-quality novel views from a single in-the-wild image. However, due to the lack of information from multiple views, these works encounter…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Yunhan Yang , Yukun Huang , Xiaoyang Wu , Yuan-Chen Guo , Song-Hai Zhang , Hengshuang Zhao , Tong He , Xihui Liu

Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains constrained by severe inference costs. Compared with image generation, video synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Shitong Shao , Lichen Bai , Pengfei Wan , James Kwok , Zeke Xie

Recent advancements in video diffusion models have shown exceptional abilities in simulating real-world dynamics and maintaining 3D consistency. This progress inspires us to investigate the potential of these models to ensure dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Jianhong Bai , Menghan Xia , Xintao Wang , Ziyang Yuan , Xiao Fu , Zuozhu Liu , Haoji Hu , Pengfei Wan , Di Zhang

We propose SparseFusion, a sparse view 3D reconstruction approach that unifies recent advances in neural rendering and probabilistic image generation. Existing approaches typically build on neural rendering with re-projected features but…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Zhizhuo Zhou , Shubham Tulsiani

The field of 4D world modeling - aiming to jointly capture spatial geometry and temporal dynamics - has witnessed remarkable progress in recent years, driven by advances in large-scale generative models and multimodal learning. However, the…

We propose UpFusion, a system that can perform novel view synthesis and infer 3D representations for an object given a sparse set of reference images without corresponding pose information. Current sparse-view 3D inference methods typically…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Bharath Raj Nagoor Kani , Hsin-Ying Lee , Sergey Tulyakov , Shubham Tulsiani

Lip synchronization is the task of aligning a speaker's lip movements in video with corresponding speech audio, and it is essential for creating realistic, expressive video content. However, existing methods often rely on reference frames…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Ziqiao Peng , Jiwen Liu , Haoxian Zhang , Xiaoqiang Liu , Songlin Tang , Pengfei Wan , Di Zhang , Hongyan Liu , Jun He

This paper introduces innovative solutions to enhance spatial controllability in diffusion models reliant on text queries. We first introduce vision guidance as a foundational spatial cue within the perturbed distribution. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zipeng Qi , Guoxi Huang , Chenyang Liu , Fei Ye

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

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

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zi-Xin Zou , Weihao Cheng , Yan-Pei Cao , Shi-Sheng Huang , Ying Shan , Song-Hai Zhang

The stylization of 3D scenes is an increasingly attractive topic in 3D vision. Although image style transfer has been extensively researched with promising results, directly applying 2D style transfer methods to 3D scenes often fails to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yushen Zuo , Jun Xiao , Kin-Chung Chan , Rongkang Dong , Cuixin Yang , Zongqi He , Hao Xie , Kin-Man Lam
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