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Recent text-to-3D methods employing diffusion models have made significant advancements in 3D human generation. However, these approaches face challenges due to the limitations of text-to-image diffusion models, which lack an understanding…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xin Huang , Ruizhi Shao , Qi Zhang , Hongwen Zhang , Ying Feng , Yebin Liu , Qing Wang

Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing ControlNet-like methods struggle with compositional visual conditioning - simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Yanjie Pan , Qingdong He , Zhengkai Jiang , Pengcheng Xu , Chaoyi Wang , Jinlong Peng , Haoxuan Wang , Yun Cao , Zhenye Gan , Mingmin Chi , Bo Peng , Yabiao Wang

Recently, diffusion models like StableDiffusion have achieved impressive image generation results. However, the generation process of such diffusion models is uncontrollable, which makes it hard to generate videos with continuous and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Zhihao Hu , Dong Xu

While modern diffusion models excel at generating high-quality and diverse images, they still struggle with high-fidelity compositional and multimodal control, particularly when users simultaneously specify text prompts, subject references,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yusuf Dalva , Guocheng Gordon Qian , Maya Goldenberg , Tsai-Shien Chen , Kfir Aberman , Sergey Tulyakov , Pinar Yanardag , Kuan-Chieh Jackson Wang

Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of text-to-4D dynamic 3D scene generation with diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Yufeng Zheng , Xueting Li , Koki Nagano , Sifei Liu , Karsten Kreis , Otmar Hilliges , Shalini De Mello

In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical rendering pipeline can be replaced by efficient models that are…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Yiyi Liao , Katja Schwarz , Lars Mescheder , Andreas Geiger

Text-to-image generation has made significant advancements with the introduction of text-to-image diffusion models. These models typically consist of a language model that interprets user prompts and a vision model that generates…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Shihao Zhao , Shaozhe Hao , Bojia Zi , Huaizhe Xu , Kwan-Yee K. Wong

Distilling 3D representations from pretrained 2D diffusion models is essential for 3D creative applications across gaming, film, and interior design. Current SDS-based methods are hindered by inefficient information distillation from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Haoran Li , Yuli Tian , Yonghui Wang , Yong Liao , Lin Wang , Yuyang Wang , Peng Yuan Zhou

Recent advances in diffusion models have significantly improved 3D generation, enabling the use of assets generated from an image for embodied AI simulations. However, the one-to-many nature of the image-to-3D problem limits their use due…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Onat Şahin , Mohammad Altillawi , George Eskandar , Carlos Carbone , Ziyuan Liu

Recent text-to-image models, such as Stable Diffusion, have achieved impressive visual quality, yet they often suffer from geometric inconsistencies that undermine the structural realism of generated scenes. One prominent issue is vanishing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Ryota Okumura , Kaede Shiohara , Toshihiko Yamasaki

Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to generate a 3D model, which lacks the control of each…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Peng Li , Suizhi Ma , Jialiang Chen , Yuan Liu , Congyi Zhang , Wei Xue , Wenhan Luo , Alla Sheffer , Wenping Wang , Yike Guo

Current diffusion-based text-to-video methods are limited to producing short video clips of a single shot and lack the capability to generate multi-shot videos with discrete transitions where the same character performs distinct activities…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Ozgur Kara , Krishna Kumar Singh , Feng Liu , Duygu Ceylan , James M. Rehg , Tobias Hinz

Recent advances in large models have significantly advanced image-to-3D reconstruction. However, the generated models are often fused into a single piece, limiting their applicability in downstream tasks. This paper focuses on 3D garment…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Xuan Li , Chang Yu , Wenxin Du , Ying Jiang , Tianyi Xie , Yunuo Chen , Yin Yang , Chenfanfu Jiang

Diffusion-based text-to-image generative models, e.g., Stable Diffusion, have revolutionized the field of content generation, enabling significant advancements in areas like image editing and video synthesis. Despite their formidable…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Yanyu Li , Xian Liu , Anil Kag , Ju Hu , Yerlan Idelbayev , Dhritiman Sagar , Yanzhi Wang , Sergey Tulyakov , Jian Ren

There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR) applications. However, today's models produce artificial environments, falling short of supporting collaborative tasks that benefit from…

Artificial Intelligence · Computer Science 2024-09-24 Nels Numan , Shwetha Rajaram , Balasaravanan Thoravi Kumaravel , Nicolai Marquardt , Andrew D. Wilson

Text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models has shown great promise but still suffers from inconsistent 3D geometric structures (Janus problems) and severe artifacts. The aforementioned problems…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Baorui Ma , Haoge Deng , Junsheng Zhou , Yu-Shen Liu , Tiejun Huang , Xinlong Wang

In this paper, we present a novel diffusion model called that generates multiview-consistent images from a single-view image. Using pretrained large-scale 2D diffusion models, recent work Zero123 demonstrates the ability to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Yuan Liu , Cheng Lin , Zijiao Zeng , Xiaoxiao Long , Lingjie Liu , Taku Komura , Wenping Wang

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei

Text-to-image diffusion models are gradually introduced into computer graphics, recently enabling the development of Text-to-3D pipelines in an open domain. However, for interactive editing purposes, local manipulations of content through a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Aryan Mikaeili , Or Perel , Mehdi Safaee , Daniel Cohen-Or , Ali Mahdavi-Amiri

We propose a simple yet effective pipeline for stylizing a 3D scene, harnessing the power of 2D image diffusion models. Given a NeRF model reconstructed from a set of multi-view images, we perform 3D style transfer by refining the source…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada
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