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DreamFusion has recently demonstrated the utility of a pre-trained text-to-image diffusion model to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesis results. However, the method has two inherent limitations:…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Chen-Hsuan Lin , Jun Gao , Luming Tang , Towaki Takikawa , Xiaohui Zeng , Xun Huang , Karsten Kreis , Sanja Fidler , Ming-Yu Liu , Tsung-Yi Lin

Text-to-3D (T23D) generation has transformed digital content creation, yet remains bottlenecked by blind trial-and-error prompting processes that yield unpredictable results. While visual prompt engineering has advanced in text-to-image…

Graphics · Computer Science 2025-08-04 Nan Xiang , Tianyi Liang , Haiwen Huang , Shiqi Jiang , Hao Huang , Yifei Huang , Liangyu Chen , Changbo Wang , Chenhui Li

3D visual grounding has made notable progress in localizing objects within complex 3D scenes. However, grounding referring expressions beyond objects in 3D scenes remains unexplored. In this paper, we introduce Anywhere3D-Bench, a holistic…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Tianxu Wang , Zhuofan Zhang , Ziyu Zhu , Yue Fan , Jing Xiong , Pengxiang Li , Xiaojian Ma , Qing Li

In recent years, the demand for 3D content has grown exponentially with the intelligent upgrade of interactive media, extended reality (XR), and Metaverse industries. In order to overcome the limitations of traditional manual modeling…

Graphics · Computer Science 2025-12-23 Xiang Tang , Ruotong Li , Xiaopeng Fan

We provide a new multi-task benchmark for evaluating text-to-image models. We perform a human evaluation comparing the most common open-source (Stable Diffusion) and commercial (DALL-E 2) models. Twenty computer science AI graduate students…

Recent progress in text-to-3D generation has been achieved through the utilization of score distillation methods: they make use of the pre-trained text-to-image (T2I) diffusion models by distilling via the diffusion model training…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Kyungmin Lee , Kihyuk Sohn , Jinwoo Shin

Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a more natural way of interaction for users. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Han Yi , Zhedong Zheng , Xiangyu Xu , Tat-seng Chua

Text-to-3D-aware face (T3D Face) generation and manipulation is an emerging research hot spot in machine learning, which still suffers from low efficiency and poor quality. In this paper, we propose an End-to-End Efficient and Effective…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Jinlu Zhang , Yiyi Zhou , Qiancheng Zheng , Xiaoxiong Du , Gen Luo , Jun Peng , Xiaoshuai Sun , Rongrong Ji

Improving visual text synthesis has long been a challenging and evolving frontier for image generation models. While recent state-of-the-art (SOTA) models have made remarkable strides in text generation capabilities, existing benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Peirong Zhang , Haowei Xu , Jiaxin Zhang , Xuhan Zheng , Guitao Xu , Yuyi Zhang , Junle Liu , Zhenhua Yang , Wei Zhou , Lianwen Jin

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

The rapid progress of large, pretrained models for both visual content generation and 3D reconstruction opens up new possibilities for text-to-3D generation. Intuitively, one could obtain a formidable 3D scene generator if one were able to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Hyojun Go , Dominik Narnhofer , Goutam Bhat , Prune Truong , Federico Tombari , Konrad Schindler

Text-to-image (T2I) models have garnered significant attention for generating high-quality images aligned with text prompts. However, rapid T2I model advancements reveal limitations in early benchmarks, lacking comprehensive evaluations,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Jingjing Chang , Yixiao Fang , Peng Xing , Shuhan Wu , Wei Cheng , Rui Wang , Xianfang Zeng , Gang Yu , Hai-Bao Chen

The rapid advancements of Text-to-Image (T2I) models have ushered in a new phase of AI-generated content, marked by their growing ability to interpret and follow user instructions. However, existing T2I model evaluation benchmarks fall…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Xinyu Wei , Jinrui Zhang , Zeqing Wang , Hongyang Wei , Zhen Guo , Lei Zhang

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

Generative models for 3D object synthesis have seen significant advancements with the incorporation of prior knowledge distilled from 2D diffusion models. Nevertheless, challenges persist in the form of multi-view geometric inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Lincong Feng , Muyu Wang , Maoyu Wang , Kuo Xu , Xiaoli Liu

AI-based text-to-image models do not only excel at generating realistic images, they also give designers more and more fine-grained control over the image content. Consequently, these approaches have gathered increased attention within the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-30 Sebastian Hartwig , Dominik Engel , Leon Sick , Hannah Kniesel , Tristan Payer , Poonam Poonam , Michael Glöckler , Alex Bäuerle , Timo Ropinski

Text-driven 3D stylization is a complex and crucial task in the fields of computer vision (CV) and computer graphics (CG), aimed at transforming a bare mesh to fit a target text. Prior methods adopt text-independent multilayer perceptrons…

Computer Vision and Pattern Recognition · Computer Science 2023-08-07 Yiwei Ma , Xiaioqing Zhang , Xiaoshuai Sun , Jiayi Ji , Haowei Wang , Guannan Jiang , Weilin Zhuang , Rongrong Ji

Text rendering has recently emerged as one of the most challenging frontiers in visual generation, drawing significant attention from large-scale diffusion and multimodal models. However, text editing within images remains largely…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Rui Gui , Yang Wan , Haochen Han , Dongxing Mao , Fangming Liu , Min Li , Alex Jinpeng Wang

Diffusion models trained on large-scale text-image datasets have demonstrated a strong capability of controllable high-quality image generation from arbitrary text prompts. However, the generation quality and generalization ability of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Ying-Tian Liu , Yuan-Chen Guo , Guan Luo , Heyi Sun , Wei Yin , Song-Hai Zhang

Despite rapid advances in 3D content generation, quality assessment for the generated 3D assets remains challenging. Existing methods mainly rely on image-based metrics and operate solely at the object level, limiting their ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Yuhan Zhang , Long Zhuo , Ziyang Chu , Tong Wu , Zhibing Li , Liang Pan , Dahua Lin , Ziwei Liu