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Related papers: Fast Multi-view Consistent 3D Editing with Video P…

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Recent advancements in diffusion models have significantly facilitated text-guided video editing. However, there is a relative scarcity of research on image-guided video editing, a method that empowers users to edit videos by merely…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Zhi-Lin Huang , Yixuan Liu , Chujun Qin , Zhongdao Wang , Dong Zhou , Dong Li , Emad Barsoum

Recent advancements in diffusion frameworks have significantly enhanced video editing, achieving high fidelity and strong alignment with textual prompts. However, conventional approaches using image diffusion models fall short in handling…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Yixuan Zhu , Haolin Wang , Shilin Ma , Wenliang Zhao , Yansong Tang , Lei Chen , Jie Zhou

Most text-to-3D generators build upon off-the-shelf text-to-image models trained on billions of images. They use variants of Score Distillation Sampling (SDS), which is slow, somewhat unstable, and prone to artifacts. A mitigation is to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Luke Melas-Kyriazi , Iro Laina , Christian Rupprecht , Natalia Neverova , Andrea Vedaldi , Oran Gafni , Filippos Kokkinos

3D editing refers to the ability to apply local or global modifications to 3D assets. Effective 3D editing requires maintaining semantic consistency by performing localized changes according to prompts, while also preserving local…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Yizhao Xu , Hongyuan Zhu , Caiyun Liu , Tianfu Wang , Keyu Chen , Sicheng Xu , Jiaolong Yang , Nicholas Jing Yuan , Qi Zhang

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

Recently, 3D content creation from text prompts has demonstrated remarkable progress by utilizing 2D and 3D diffusion models. While 3D diffusion models ensure great multi-view consistency, their ability to generate high-quality and diverse…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Fangfu Liu , Diankun Wu , Yi Wei , Yongming Rao , Yueqi Duan

Single-image 3D reconstruction remains a fundamental challenge in computer vision due to inherent geometric ambiguities and limited viewpoint information. Recent advances in Latent Video Diffusion Models (LVDMs) offer promising 3D priors…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yabo Chen , Chen Yang , Jiemin Fang , Xiaopeng Zhang , Lingxi Xie , Wei Shen , Wenrui Dai , Hongkai Xiong , Qi Tian

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

This paper presents Video-P2P, a novel framework for real-world video editing with cross-attention control. While attention control has proven effective for image editing with pre-trained image generation models, there are currently no…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Shaoteng Liu , Yuechen Zhang , Wenbo Li , Zhe Lin , Jiaya Jia

Recent innovations on text-to-3D generation have featured Score Distillation Sampling (SDS), which enables the zero-shot learning of implicit 3D models (NeRF) by directly distilling prior knowledge from 2D diffusion models. However, current…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yang Chen , Yingwei Pan , Haibo Yang , Ting Yao , Tao Mei

Recent advances in video generation have been dominated by diffusion and flow-matching models, which produce high-quality results but remain computationally intensive and difficult to scale. In this work, we introduce VideoAR, the first…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Longbin Ji , Xiaoxiong Liu , Junyuan Shang , Shuohuan Wang , Yu Sun , Hua Wu , Haifeng Wang

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compositing pipeline: (i) segmenting and converting visual inputs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiacheng Chen , Ramin Mehran , Xuhui Jia , Saining Xie , Sanghyun Woo

Despite the fact that text-to-video (TTV) model has recently achieved remarkable success, there have been few approaches on TTV for its extension to video editing. Motivated by approaches on TTV models adapting from diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Chaehun Shin , Heeseung Kim , Che Hyun Lee , Sang-gil Lee , Sungroh Yoon

Video diffusion models have recently enabled high-quality video generation with ViT-based architectures, but remain computationally intensive because generation requires attention computation over long spatiotemporal sequences. Token…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Sheng Li , Yang Sui , Junhao Ran , Bo Yuan , Yue Dai , Xulong Tang

Recent developments in Multimodal Large Language Models (MLLMs) have significantly improved Vision-Language (VL) reasoning in 2D domains. However, extending these capabilities to 3D scene understanding remains a major challenge. Existing 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Haijier Chen , Bo Xu , Shoujian Zhang , Haoze Liu , Jiaxuan Lin , Jingrong Wang

Text-to-3D with diffusion models has achieved remarkable progress in recent years. However, existing methods either rely on score distillation-based optimization which suffer from slow inference, low diversity and Janus problems, or are…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jiahao Li , Hao Tan , Kai Zhang , Zexiang Xu , Fujun Luan , Yinghao Xu , Yicong Hong , Kalyan Sunkavalli , Greg Shakhnarovich , Sai Bi

Despite the typical inversion-then-editing paradigm using text-to-image (T2I) models has demonstrated promising results, directly extending it to text-to-video (T2V) models still suffers severe artifacts such as color flickering and content…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Yukun Wang , Longguang Wang , Zhiyuan Ma , Qibin Hu , Kai Xu , Yulan Guo

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim

Image generation and editing have seen a great deal of advancements with the rise of large-scale diffusion models that allow user control of different modalities such as text, mask, depth maps, etc. However, controlled editing of videos…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 AmirHossein Zamani , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

We introduce MultiDiff, a novel approach for consistent novel view synthesis of scenes from a single RGB image. The task of synthesizing novel views from a single reference image is highly ill-posed by nature, as there exist multiple,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Norman Müller , Katja Schwarz , Barbara Roessle , Lorenzo Porzi , Samuel Rota Bulò , Matthias Nießner , Peter Kontschieder