Search Results for author:
Found 17 papers, 9 papers with code
Point-NeRF: Point-based Neural Radiance Fields
Point-NeRF combines the advantages of these two approaches by using neural 3D point clouds, with associated neural features, to model a radiance field.
Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
Our synergy process leverages a representation cycle for 3DMM parameters and 3D landmarks.
Ranked #1 on
Face Alignment
on AFLW
DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction
Reconstructing 3D shapes from single-view images has been a long-standing research problem.
Ranked #1 on
Single-View 3D Reconstruction
on ShapeNetCore
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
Finally, the probability of occupancy is also integrated into a proposal refinement module to generate the final bounding boxes.
Ranked #2 on
3D Object Detection
on KITTI Cars Moderate
Grid-GCN for Fast and Scalable Point Cloud Learning
Compared with popular sampling methods such as Farthest Point Sampling (FPS) and Ball Query, CAGQ achieves up to 50X speed-up.
Strivec: Sparse Tri-Vector Radiance Fields
In contrast to TensoRF which uses a global tensor and focuses on their vector-matrix decomposition, we propose to utilize a cloud of local tensors and apply the classic CANDECOMP/PARAFAC (CP) decomposition to factorize each tensor into triple vectors that express local feature distributions along spatial axes and compactly encode a local neural field.
Accurate 3D Facial Geometry Prediction by Multi-Task, Multi-Modal, and Multi-Representation Landmark Refinement Network
This work focuses on complete 3D facial geometry prediction, including 3D facial alignment via 3D face modeling and face orientation estimation using the proposed multi-task, multi-modal, and multi-representation landmark refinement network (M$^3$-LRN).
Geometry-Aware Instance Segmentation with Disparity Maps
Mask regression is based on 2D, 2. 5D, and 3D ROI using the pseudo-lidar and image-based representations.
Ranked #16 on
Instance Segmentation
on Cityscapes val
(using extra training data)
Report: Dynamic Eye Movement Matching and Visualization Tool in Neuro Gesture
In the research of the impact of gestures using by a lecturer, one challenging task is to infer the attention of a group of audiences.
Generative Cooperative Net for Image Generation and Data Augmentation
In this paper, we explore a generative model for the task of generating unseen images with desired features.
Stochastic Dynamics for Video Infilling
In this paper, we introduce a stochastic dynamics video infilling (SDVI) framework to generate frames between long intervals in a video.
SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation
On the Waymo Open Dataset and KITTI, SPG improves 3D detection results of these two methods across all categories.
Ranked #5 on
3D Object Detection
on KITTI Cars Moderate
Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and Editing
We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility.
MVDD: Multi-View Depth Diffusion Models
State-of-the-art results from extensive experiments demonstrate MVDD's excellent ability in 3D shape generation, depth completion, and its potential as a 3D prior for downstream tasks.
One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation
Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability.
GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation
While the optimization can draw photometric reference from the input videos or be regulated by generative models, directly supervising Gaussian motions remains underexplored.
MagicMirror: Fast and High-Quality Avatar Generation with a Constrained Search Space
We introduce a novel framework for 3D human avatar generation and personalization, leveraging text prompts to enhance user engagement and customization.
