Search Results for author:
Found 23 papers, 14 papers with code
TimeWalker: Personalized Neural Space for Lifelong Head Avatars
At the heart of TimeWalker's success is a novel neural parametric model that learns personalized representation with the disentanglement of shape, expression, and appearance across ages.
Urban Architect: Steerable 3D Urban Scene Generation with Layout Prior
(2) To handle the unbounded nature of urban scenes, we represent 3D scene with a Scalable Hash Grid structure, incrementally adapting to the growing scale of urban scenes.
CosmicMan: A Text-to-Image Foundation Model for Humans
We present CosmicMan, a text-to-image foundation model specialized for generating high-fidelity human images.
Parameterization-driven Neural Surface Reconstruction for Object-oriented Editing in Neural Rendering
The advancements in neural rendering have increased the need for techniques that enable intuitive editing of 3D objects represented as neural implicit surfaces.
UnitedHuman: Harnessing Multi-Source Data for High-Resolution Human Generation
A holistic human dataset inevitably has insufficient and low-resolution information on local parts.
Urban Radiance Field Representation with Deformable Neural Mesh Primitives
To construct urban-level radiance fields efficiently, we design Deformable Neural Mesh Primitive~(DNMP), and propose to parameterize the entire scene with such primitives.
DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
Realistic human-centric rendering plays a key role in both computer vision and computer graphics.
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
It is a large-scale digital library for head avatars with three key attributes: 1) High Fidelity: all subjects are captured by 60 synchronized, high-resolution 2K cameras in 360 degrees.
MonoHuman: Animatable Human Neural Field from Monocular Video
Recent works propose to graft a deformation network into the NeRF to further model the dynamics of the human neural field for animating vivid human motions.
Deformable Model-Driven Neural Rendering for High-Fidelity 3D Reconstruction of Human Heads Under Low-View Settings
To address this, we propose geometry decomposition and adopt a two-stage, coarse-to-fine training strategy, allowing for progressively capturing high-frequency geometric details.
Generalizable Neural Performer: Learning Robust Radiance Fields for Human Novel View Synthesis
Specifically, we compress the light fields for novel view human rendering as conditional implicit neural radiance fields from both geometry and appearance aspects.
StyleGAN-Human: A Data-Centric Odyssey of Human Generation
In addition, a model zoo and human editing applications are demonstrated to facilitate future research in the community.
Simulating Fluids in Real-World Still Images
In this work, we tackle the problem of real-world fluid animation from a still image.
Learning a Structured Latent Space for Unsupervised Point Cloud Completion
Specifically, we map a series of related partial point clouds into multiple complete shape and occlusion code pairs and fuse the codes to obtain their representations in the unified latent space.
RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimization
The correspondence field estimation and pose refinement are conducted alternatively in each iteration to recover the object poses.
Ranked #1 on
6D Pose Estimation using RGB
on LineMOD
Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
The key insight is that we decouple the instances from a coarsely completed semantic scene instead of a raw input image to guide the reconstruction of instances and the overall scene.
Ranked #2 on
3D Semantic Scene Completion
on NYUv2
SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural Networks
To suit our network to self-supervised learning, we design several novel loss functions that utilize the inherent properties of LiDAR point clouds.
Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
Depth information has proven to be a useful cue in the semantic segmentation of RGB-D images for providing a geometric counterpart to the RGB representation.
Ranked #1 on
Semantic Segmentation
on TLCGIS
3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior
To this end, we first propose a novel 3D sketch-aware feature embedding to explicitly encode geometric information effectively and efficiently.
3D Semantic Scene Completion from a single RGB image
Hallucination
TRB: A Novel Triplet Representation for Understanding 2D Human Body
In this paper, we propose the Triplet Representation for Body (TRB) -- a compact 2D human body representation, with skeleton keypoints capturing human pose information and contour keypoints containing human shape information.
Conditional Image Generation
Open-Ended Question Answering
+1
Make a Face: Towards Arbitrary High Fidelity Face Manipulation
Recent studies have shown remarkable success in face manipulation task with the advance of GANs and VAEs paradigms, but the outputs are sometimes limited to low-resolution and lack of diversity.
Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation
Recent studies have shown remarkable advances in 3D human pose estimation from monocular images, with the help of large-scale in-door 3D datasets and sophisticated network architectures.
Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning
No-reference image quality assessment (NR-IQA) is a fundamental yet challenging task in low-level computer vision community.
