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Recent advancements in vision-language foundation models have significantly enhanced open-vocabulary 3D scene understanding. However, the generalizability of existing methods is constrained due to their framework designs and their reliance…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Yunsong Wang , Hanlin Chen , Gim Hee Lee

Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-fidelity and 3D-consistent novel-view frames. However, they…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jaehoon Ko , Kyusun Cho , Joungbin Lee , Heeji Yoon , Sangmin Lee , Sangjun Ahn , Seungryong Kim

Modern machine learning models for scene understanding, such as depth estimation and object tracking, rely on large, high-quality datasets that mimic real-world deployment scenarios. To address data scarcity, we propose an end-to-end system…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Sonia Laguna , Alberto Garcia-Garcia , Marie-Julie Rakotosaona , Stylianos Moschoglou , Leonhard Helminger , Sergio Orts-Escolano

Recent advancements in zero-shot speech generation have enabled models to synthesize speech that mimics speaker identity and speaking style from speech prompts. However, these models' effectiveness is significantly limited in real-world…

Audio and Speech Processing · Electrical Eng. & Systems 2025-08-14 Boyu Zhu , Cheng Gong , Muyang Wu , Ruihao Jing , Fan Liu , Xiaolei Zhang , Chi Zhang , Xuelong Li

We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only $1$ minute.The key component is a dual-mode multi-view latent diffusion model. Given the noisy multi-view latents, the 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Xinyang Li , Zhangyu Lai , Linning Xu , Jianfei Guo , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

This paper presents a novel latent 3D diffusion model for the generation of neural voxel fields, aiming to achieve accurate part-aware structures. Compared to existing methods, there are two key designs to ensure high-quality and accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Yuhang Huang , SHilong Zou , Xinwang Liu , Kai Xu

This paper introduces a pioneering 3D volumetric encoder designed for text-to-3D generation. To scale up the training data for the diffusion model, a lightweight network is developed to efficiently acquire feature volumes from multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Zhicong Tang , Shuyang Gu , Chunyu Wang , Ting Zhang , Jianmin Bao , Dong Chen , Baining Guo

Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate objects, and few generate both. The generated scene layout…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Zhenggang Tang , Yuehao Wang , Yuchen Fan , Jun-Kun Chen , Yu-Ying Yeh , Kihyuk Sohn , Zhangyang Wang , Qixing Huang , Alexander Schwing , Rakesh Ranjan , Dilin Wang , Zhicheng Yan

We tackle the problem of generating audio samples conditioned on descriptive text captions. In this work, we propose AaudioGen, an auto-regressive generative model that generates audio samples conditioned on text inputs. AudioGen operates…

Generating high-fidelity, seamless textures directly on 3D surfaces, what we term 3D-native texturing, remains a fundamental open challenge, with the potential to overcome long-standing limitations of UV-based and multi-view projection…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chia-Hao Chen , Zi-Xin Zou , Yan-Pei Cao , Ze Yuan , Guan Luo , Xiaojuan Qi , Ding Liang , Song-Hai Zhang , Yuan-Chen Guo

Open-vocabulary 3D segmentation is a fundamental yet challenging task, requiring a mutual understanding of both segmentation and language. However, existing Gaussian-splatting-based methods rely either on a single 3D language field, leading…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Runsong Zhu , Ka-Hei Hui , Zhengzhe Liu , Qianyi Wu , Weiliang Tang , Shi Qiu , Pheng-Ann Heng , Chi-Wing Fu

Recent 3D human generative models have achieved remarkable progress by learning 3D-aware GANs from 2D images. However, existing 3D human generative methods model humans in a compact 1D latent space, ignoring the articulated structure and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Tao Hu , Fangzhou Hong , Ziwei Liu

This paper proposes a hierarchical generative model with a multi-grained latent variable to synthesize expressive speech. In recent years, fine-grained latent variables are introduced into the text-to-speech synthesis that enable the fine…

Audio and Speech Processing · Electrical Eng. & Systems 2021-12-28 Yukiya Hono , Kazuna Tsuboi , Kei Sawada , Kei Hashimoto , Keiichiro Oura , Yoshihiko Nankaku , Keiichi Tokuda

Currently, many multi-speaker speech synthesis and voice conversion systems address speaker variations with an embedding vector. Modeling it directly allows new voices outside of training data to be synthesized. GMM based approaches such as…

Sound · Computer Science 2023-09-26 Yao Shi , Ming Li

We train a feed-forward text-to-3D diffusion generator for human characters using only single-view 2D data for supervision. Existing 3D generative models cannot yet match the fidelity of image or video generative models. State-of-the-art 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Souhaib Attaiki , Paul Guerrero , Duygu Ceylan , Niloy J. Mitra , Maks Ovsjanikov

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

Foley sound generation aims to synthesise the background sound for multimedia content. Previous models usually employ a large development set with labels as input (e.g., single numbers or one-hot vector). In this work, we propose a…

Sound · Computer Science 2023-09-19 Yi Yuan , Haohe Liu , Xubo Liu , Xiyuan Kang , Peipei Wu , Mark D. Plumbley , Wenwu Wang

Text-guided 3D object generation aims to generate 3D objects described by user-defined captions, which paves a flexible way to visualize what we imagined. Although some works have been devoted to solving this challenging task, these works…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Zutao Jiang , Guansong Lu , Xiaodan Liang , Jihua Zhu , Wei Zhang , Xiaojun Chang , Hang Xu

Recently, the field of text-guided 3D scene generation has garnered significant attention. High-quality generation that aligns with physical realism and high controllability is crucial for practical 3D scene applications. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yang Zhou , Zongjin He , Qixuan Li , Chao Wang

The ability to generate 3D multiphase microstructures on-demand with targeted attributes can greatly accelerate the design of advanced materials. Here, we present a conditional latent diffusion model (LDM) framework that rapidly synthesizes…

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