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This paper introduces StructDiff, a generative framework based on a single-scale diffusion model for single-image generation. Single-image generation aims to synthesize diverse samples with similar visual content to the source image by…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Yinxi He , Kang Liao , Chunyu Lin , Tianyi Wei , Yao Zhao

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

Dynamic novel view synthesis aims to capture the temporal evolution of visual content within videos. Existing methods struggle to distinguishing between motion and structure, particularly in scenarios where camera poses are either unknown…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Chaoyang Wang , Peiye Zhuang , Aliaksandr Siarohin , Junli Cao , Guocheng Qian , Hsin-Ying Lee , Sergey Tulyakov

We propose a method for generating fly-through videos of a scene, from a single image and a given camera trajectory. We build upon an image-to-video latent diffusion model. We condition its UNet denoiser on the camera trajectory, using four…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Stefan Popov , Amit Raj , Michael Krainin , Yuanzhen Li , William T. Freeman , Michael Rubinstein

Crafting magic and illusions is one of the most thrilling aspects of filmmaking, with visual effects (VFX) serving as the powerhouse behind unforgettable cinematic experiences. While recent advances in generative artificial intelligence…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Xinyu Liu , Ailing Zeng , Wei Xue , Harry Yang , Wenhan Luo , Qifeng Liu , Yike Guo

Generating a complete and explorable 360-degree visual world enables a wide range of downstream applications. While prior works have advanced the field, they remain constrained by either narrow field-of-view limitations, which hinder the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Yuyang Yin , HaoXiang Guo , Fangfu Liu , Mengyu Wang , Hanwen Liang , Eric Li , Yikai Wang , Xiaojie Jin , Yao Zhao , Yunchao Wei

Envisioning physically plausible outcomes from a single image requires a deep understanding of the world's dynamics. To address this, we introduce PhysGen3D, a novel framework that transforms a single image into an amodal, camera-centric,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Boyuan Chen , Hanxiao Jiang , Shaowei Liu , Saurabh Gupta , Yunzhu Li , Hao Zhao , Shenlong Wang

3D content generation has recently attracted significant research interest, driven by its critical applications in VR/AR and embodied AI. In this work, we tackle the challenging task of synthesizing multiple 3D assets within a single scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yanxu Meng , Haoning Wu , Ya Zhang , Weidi Xie

Recent advancements in 4D scene reconstruction, particularly those leveraging diffusion priors, have shown promise for novel view synthesis in autonomous driving. However, these methods often process frames independently or in a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Heyu Si , Brandon James Denis , Muyang Sun , Dragos Datcu , Yaoru Li , Xin Jin , Ruiju Fu , Yuliia Tatarinova , Federico Landi , Jie Song , Mingli Song , Qi Guo

Recent progress in 3D/4D scene generation emphasizes the importance of physical alignment throughout video generation and scene reconstruction. However, existing methods improve the alignment separately at each stage, making it difficult to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Byeongjun Park , Hyojun Go , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos using a base video generation model and a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Jonathan Ho , William Chan , Chitwan Saharia , Jay Whang , Ruiqi Gao , Alexey Gritsenko , Diederik P. Kingma , Ben Poole , Mohammad Norouzi , David J. Fleet , Tim Salimans

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models. Generally, incorporating 3D representations into diffusion model decrease the model's speed as well as…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Emmanuelle Bourigault , Pauline Bourigault

Recent advancements in 3D diffusion-based semantic scene generation have gained attention. However, existing methods rely on unconditional generation and require multiple resampling steps when editing scenes, which significantly limits…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Haowen Zheng , Yanyan Liang

Diffusion models (DMs) excel in photo-realistic image synthesis, but their adaptation to LiDAR scene generation poses a substantial hurdle. This is primarily because DMs operating in the point space struggle to preserve the curve-like…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Haoxi Ran , Vitor Guizilini , Yue Wang

In this work, we introduce 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 3D geometry…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Xiaoxiao Long , Yuan-Chen Guo , Cheng Lin , Yuan Liu , Zhiyang Dou , Lingjie Liu , Yuexin Ma , Song-Hai Zhang , Marc Habermann , Christian Theobalt , Wenping Wang

We present 3DScenePrompt, a framework that generates the next video chunk from arbitrary-length input while enabling precise camera control and preserving scene consistency. Unlike methods conditioned on a single image or a short clip, we…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 JoungBin Lee , Jaewoo Jung , Jisang Han , Takuya Narihira , Kazumi Fukuda , Junyoung Seo , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

Single-view 3D reconstruction is currently approached from two dominant perspectives: reconstruction of scenes with limited diversity using 3D data supervision or reconstruction of diverse singular objects using large image priors. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Andreea Ardelean , Mert Özer , Bernhard Egger

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo

Generating 3D scenes is a challenging open problem, which requires synthesizing plausible content that is fully consistent in 3D space. While recent methods such as neural radiance fields excel at view synthesis and 3D reconstruction, they…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Titas Anciukevičius , Fabian Manhardt , Federico Tombari , Paul Henderson
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