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Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

Current controls over diffusion models (e.g., through text or ControlNet) for image generation fall short in recognizing abstract, continuous attributes like illumination direction or non-rigid shape change. In this paper, we present an…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Ta-Ying Cheng , Matheus Gadelha , Thibault Groueix , Matthew Fisher , Radomir Mech , Andrew Markham , Niki Trigoni

Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question of adding such controllability to text-to-3D generation. In…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Sungwon Hwang , Junha Hyung , Jaegul Choo

Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary paradigms dominate the field of text-to-3D: the feed-forward generation solutions, capable of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Yonghao Yu , Shunan Zhu , Huai Qin , Haorui Li

Text-to-image generation has witnessed great progress, especially with the recent advancements in diffusion models. Since texts cannot provide detailed conditions like object appearance, reference images are usually leveraged for the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zhiqi Huang , Huixin Xiong , Haoyu Wang , Longguang Wang , Zhiheng Li

With the rapid advancement of 3D representation techniques and generative models, substantial progress has been made in reconstructing full-body 3D avatars from a single image. However, this task remains fundamentally ill-posedness due to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Gaofeng Liu , Hengsen Li , Ruoyu Gao , Xuetong Li , Zhiyuan Ma , Tao Fang

Text-to-image generation has made remarkable progress with the emergence of diffusion models. However, it is still a difficult task to generate images for street views based on text, mainly because the road topology of street scenes is…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Jinming Su , Songen Gu , Yiting Duan , Xingyue Chen , Junfeng Luo

Customized text-to-video generation aims to generate text-guided videos with user-given subjects, which has gained increasing attention. However, existing works are primarily limited to single-subject oriented text-to-video generation,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Hong Chen , Xin Wang , Guanning Zeng , Yipeng Zhang , Yuwei Zhou , Feilin Han , Yaofei Wu , Wenwu Zhu

Current text-to-image generation models often struggle to follow textual instructions, especially the ones requiring spatial reasoning. On the other hand, Large Language Models (LLMs), such as GPT-4, have shown remarkable precision in…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Tianjun Zhang , Yi Zhang , Vibhav Vineet , Neel Joshi , Xin Wang

Recent advances in vision-language models have facilitated progress in sketch generation. However, existing specialized methods primarily focus on generic synthesis and lack mechanisms for precise control over sketch styles. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Tengjie Li , Shikui Tu , Lei Xu

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee

Score Distillation Sampling (SDS) by well-trained 2D diffusion models has shown great promise in text-to-3D generation. However, this paradigm distills view-agnostic 2D image distributions into the rendering distribution of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Chenhan Jiang , Yihan Zeng , Tianyang Hu , Songcun Xu , Wei Zhang , Hang Xu , Dit-Yan Yeung

In recent times, automatic text-to-3D content creation has made significant progress, driven by the development of pretrained 2D diffusion models. Existing text-to-3D methods typically optimize the 3D representation to ensure that the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yiwei Ma , Yijun Fan , Jiayi Ji , Haowei Wang , Xiaoshuai Sun , Guannan Jiang , Annan Shu , Rongrong Ji

Recent methods such as Score Distillation Sampling (SDS) and Variational Score Distillation (VSD) using 2D diffusion models for text-to-3D generation have demonstrated impressive generation quality. However, the long generation time of such…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Linqi Zhou , Andy Shih , Chenlin Meng , Stefano Ermon

Text-to-image diffusion models have made significant progress in image generation, allowing for effortless customized generation. However, existing image editing methods still face certain limitations when dealing with personalized image…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Yuhong Zhang , Han Wang , Yiwen Wang , Rong Xie , Li Song

Recently, text-to-3D approaches have achieved high-fidelity 3D content generation using text description. However, the generated objects are stochastic and lack fine-grained control. Sketches provide a cheap approach to introduce such…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Minglin Chen , Weihao Yuan , Yukun Wang , Zhe Sheng , Yisheng He , Zilong Dong , Liefeng Bo , Yulan Guo

In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiaolong Li , Jiawei Mo , Ying Wang , Chethan Parameshwara , Xiaohan Fei , Ashwin Swaminathan , CJ Taylor , Zhuowen Tu , Paolo Favaro , Stefano Soatto

The controllability of 3D object generation methods is achieved through input text. Existing text-to-3D object generation methods primarily focus on generating a single object based on a single object description. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Shaorong Sun , Shuchao Pang , Yazhou Yao , Xiaoshui Huang

Text-driven 3D scene generation techniques have made rapid progress in recent years. Their success is mainly attributed to using existing generative models to iteratively perform image warping and inpainting to generate 3D scenes. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Frank Zhang , Yibo Zhang , Quan Zheng , Rui Ma , Wei Hua , Hujun Bao , Weiwei Xu , Changqing Zou

Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand in stark contrast to the compact, structured, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuan Li , Cheng Lin , Yuan Liu , Xiaoxiao Long , Chenxu Zhang , Ningna Wang , Xin Li , Wenping Wang , Xiaohu Guo