no code implementations • 25 Apr 2024 • Junting Dong, Qi Fang, Zehuan Huang, Xudong Xu, Jingbo Wang, Sida Peng, Bo Dai
Previous works usually encode the human body and clothes as a holistic model and generate the whole model in a single-stage optimization, which makes them struggle for clothing editing and meanwhile lose fine-grained control over the whole generation process.
no code implementations • 18 Mar 2024 • Zhaoyang Lyu, Ben Fei, Jinyi Wang, Xudong Xu, Ya zhang, Weidong Yang, Bo Dai
Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares.
no code implementations • 12 Dec 2023 • Kaiwen Zhang, Yifan Zhou, Xudong Xu, Xingang Pan, Bo Dai
Our key idea is to capture the semantics of the two images by fitting two LoRAs to them respectively, and interpolate between both the LoRA parameters and the latent noises to ensure a smooth semantic transition, where correspondence automatically emerges without the need for annotation.
1 code implementation • NeurIPS 2023 • Xudong Xu, Dejan Markovic, Jacob Sandakly, Todd Keebler, Steven Krenn, Alexander Richard
While 3D human body modeling has received much attention in computer vision, modeling the acoustic equivalent, i. e. modeling 3D spatial audio produced by body motion and speech, has fallen short in the community.
no code implementations • 18 Aug 2023 • Xudong Xu, Zhaoyang Lyu, Xingang Pan, Bo Dai
In this work, we propose Material-Aware Text-to-3D via LAtent BRDF auto-EncodeR (\textbf{MATLABER}) that leverages a novel latent BRDF auto-encoder for material generation.
no code implementations • 19 Apr 2023 • Zhuo Chen, Xudong Xu, Yichao Yan, Ye Pan, Wenhan Zhu, Wayne Wu, Bo Dai, Xiaokang Yang
While the use of 3D-aware GANs bypasses the requirement of 3D data, we further alleviate the necessity of style images with the CLIP model being the stylization guidance.
1 code implementation • 26 Aug 2022 • Tong Wu, Jiaqi Wang, Xingang Pan, Xudong Xu, Christian Theobalt, Ziwei Liu, Dahua Lin
Previous methods based on neural volume rendering mostly train a fully implicit model with MLPs, which typically require hours of training for a single scene.
1 code implementation • 25 May 2022 • Zhaoyang Lyu, Xudong Xu, Ceyuan Yang, Dahua Lin, Bo Dai
By modeling the reverse process of gradually diffusing the data distribution into a Gaussian distribution, generating a sample in DDPMs can be regarded as iteratively denoising a randomly sampled Gaussian noise.
1 code implementation • ICLR 2022 • Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin
The RFNet refines the coarse output of the CGNet and further improves quality of the completed point cloud.
1 code implementation • NeurIPS 2021 • Xudong Xu, Xingang Pan, Dahua Lin, Bo Dai
In this paper, we propose Generative Occupancy Fields (GOF), a novel model based on generative radiance fields that can learn compact object surfaces without impeding its training convergence.
1 code implementation • NeurIPS 2021 • Xingang Pan, Xudong Xu, Chen Change Loy, Christian Theobalt, Bo Dai
Motivated by the observation that a 3D object should look realistic from multiple viewpoints, these methods introduce a multi-view constraint as regularization to learn valid 3D radiance fields from 2D images.
no code implementations • CVPR 2021 • Xudong Xu, Hang Zhou, Ziwei Liu, Bo Dai, Xiaogang Wang, Dahua Lin
Moreover, combined with binaural recordings, our method is able to further boost the performance of binaural audio generation under supervised settings.
no code implementations • ECCV 2020 • Hang Zhou, Xudong Xu, Dahua Lin, Xiaogang Wang, Ziwei Liu
Stereophonic audio is an indispensable ingredient to enhance human auditory experience.
no code implementations • ICCV 2019 • Hang Zhou, Ziwei Liu, Xudong Xu, Ping Luo, Xiaogang Wang
Extensive experiments demonstrate that our framework is capable of inpainting realistic and varying audio segments with or without visual contexts.
1 code implementation • ICCV 2019 • Xudong Xu, Bo Dai, Dahua Lin
Sounds provide rich semantics, complementary to visual data, for many tasks.
1 code implementation • IEEE International Conference on Systems, Man and Cybernetics (SMC) 2017 • Yuenan Hou, Lifeng Liu, Qing Wei, Xudong Xu, Chunlin Chen
Recently, a state-of-the-art algorithm, called deep deterministic policy gradient (DDPG), has achieved good performance in many continuous control tasks in the MuJoCo simulator.