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This paper explores multi-modal controllable Text-to-Speech Synthesis (TTS) where the voice can be generated from face image, and the characteristics of output speech (e.g., pace, noise level, distance, tone, place) can be controllable with…

Audio and Speech Processing · Electrical Eng. & Systems 2025-05-27 Minsu Kim , Pingchuan Ma , Honglie Chen , Stavros Petridis , Maja Pantic

Recent text-to-3D generation methods achieve impressive 3D content creation capacity thanks to the advances in image diffusion models and optimizing strategies. However, current methods struggle to generate correct 3D content for a complex…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Xinhua Cheng , Tianyu Yang , Jianan Wang , Yu Li , Lei Zhang , Jian Zhang , Li Yuan

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu Zhang

Recent text-to-image generation favors various forms of spatial conditions, e.g., masks, bounding boxes, and key points. However, the majority of the prior art requires form-specific annotations to fine-tune the original model, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Z. Zhang , B. Liu , J. Bao , L. Chen , S. Zhu , J. Yu

Recent developments in 3D reconstruction and neural rendering have significantly propelled the capabilities of photo-realistic 3D scene rendering across various academic and industrial fields. The 3D Gaussian Splatting technique, alongside…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zexu Huang , Min Xu , Stuart Perry

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

In Natural Language Processing (NLP), Large Language Models (LLMs) have demonstrated high text generation quality. However, in real-world applications, LLMs must meet increasingly complex requirements. Beyond avoiding misleading or…

Computation and Language · Computer Science 2024-08-23 Xun Liang , Hanyu Wang , Yezhaohui Wang , Shichao Song , Jiawei Yang , Simin Niu , Jie Hu , Dan Liu , Shunyu Yao , Feiyu Xiong , Zhiyu Li

Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high quality, consistency, and editing flexibility. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Haoran Li , Haolin Shi , Wenli Zhang , Wenjun Wu , Yong Liao , Lin Wang , Lik-hang Lee , Pengyuan Zhou

Feed-forward 3D reconstruction offers substantial runtime advantages over per-scene optimization, which remains slow at inference and often fragile under sparse views. However, existing feed-forward methods still have potential for further…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianyu Chen , Wei Xiang , Kang Han , Yu Lu , Di Wu , Gaowen Liu , Ramana Rao Kompella

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 image generation have achieved remarkable visual quality, while a fundamental challenge remains: Can image generation be controlled at the element level, enabling intuitive modifications such as adjusting shapes, altering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Lanqing Guo , Xi Liu , Yufei Wang , Zhihao Li , Siyu Huang

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

As humans, we aspire to create media content that is both freely willed and readily controlled. Thanks to the prominent development of generative techniques, we now can easily utilize 2D diffusion methods to synthesize images controlled by…

Graphics · Computer Science 2024-05-15 Wenqi Dong , Bangbang Yang , Lin Ma , Xiao Liu , Liyuan Cui , Hujun Bao , Yuewen Ma , Zhaopeng Cui

Text-driven 3D indoor scene generation is useful for gaming, the film industry, and AR/VR applications. However, existing methods cannot faithfully capture the room layout, nor do they allow flexible editing of individual objects in the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Chuan Fang , Yuan Dong , Kunming Luo , Xiaotao Hu , Rakesh Shrestha , Ping Tan

The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios. While recent advancements in text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Yixun Liang , Xin Yang , Jiantao Lin , Haodong Li , Xiaogang Xu , Yingcong Chen

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. Additionally, 3D scene generation is vital for advancing embodied AI and world models, which depend…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yuxin Zhang , Ziyu Lu , Hongbo Duan , Keyu Fan , Pengting Luo , Peiyu Zhuang , Mengyu Yang , Houde Liu

In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models. Recent progress (Magic3D) in text-to-3D has shown that employing high-resolution (e.g., 512 x…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Jinbo Wu , Xiaobo Gao , Xing Liu , Zhengyang Shen , Chen Zhao , Haocheng Feng , Jingtuo Liu , Errui Ding

Text-guided diffusion models have revolutionized image and video generation and have also been successfully used for optimization-based 3D object synthesis. Here, we instead focus on the underexplored text-to-4D setting and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Huan Ling , Seung Wook Kim , Antonio Torralba , Sanja Fidler , Karsten Kreis

Recent advances in NeRF and 3DGS have significantly enhanced the efficiency and quality of 3D content synthesis. However, efficient personalization of generated 3D content remains a critical challenge. Current 3D personalization approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Qi Song , Ziyuan Luo , Ka Chun Cheung , Simon See , Renjie Wan

The increasing prominence of e-commerce has underscored the importance of Virtual Try-On (VTON). However, previous studies predominantly focus on the 2D realm and rely heavily on extensive data for training. Research on 3D VTON primarily…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Haodong Chen , Yongle Huang , Haojian Huang , Xiangsheng Ge , Dian Shao
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