Search Results for author:
Found 16 papers, 8 papers with code
TELA: Text to Layer-wise 3D Clothed Human Generation
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.
GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulation
Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares.
DiffMorpher: Unleashing the Capability of Diffusion Models for Image Morphing
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.
Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio
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.
MATLABER: Material-Aware Text-to-3D via LAtent BRDF auto-EncodeR
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.
HyperStyle3D: Text-Guided 3D Portrait Stylization via Hypernetworks
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.
Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction
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.
Accelerating Diffusion Models via Early Stop of the Diffusion Process
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.
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
The RFNet refines the coarse output of the CGNet and further improves quality of the completed point cloud.
Generative Occupancy Fields for 3D Surface-Aware Image Synthesis
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.
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
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.
Visually Informed Binaural Audio Generation without Binaural Audios
Moreover, combined with binaural recordings, our method is able to further boost the performance of binaural audio generation under supervised settings.
Sep-Stereo: Visually Guided Stereophonic Audio Generation by Associating Source Separation
Stereophonic audio is an indispensable ingredient to enhance human auditory experience.
Vision-Infused Deep Audio Inpainting
Extensive experiments demonstrate that our framework is capable of inpainting realistic and varying audio segments with or without visual contexts.
Recursive Visual Sound Separation Using Minus-Plus Net
Sounds provide rich semantics, complementary to visual data, for many tasks.
A novel DDPG method with prioritized experience replay
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.
