About
Benchmarks
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Subtasks
Datasets
Greatest papers with code
PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
CVPR 2020
• facebookresearch/pifuhd
• 
Although current approaches have demonstrated the potential in real world settings, they still fail to produce reconstructions with the level of detail often present in the input images.
3D HUMAN POSE ESTIMATION 3D OBJECT RECONSTRUCTION FROM A SINGLE IMAGE 3D SHAPE RECONSTRUCTION
VIBE: Video Inference for Human Body Pose and Shape Estimation
Human motion is fundamental to understanding behavior.
Ranked #6 on
3D Human Pose Estimation
on 3DPW
(using extra training data)
3D POSE ESTIMATION 3D SHAPE RECONSTRUCTION MONOCULAR 3D HUMAN POSE ESTIMATION MOTION CAPTURE
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
• facebookresearch/SparseConvNet
•
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database.
3D PART SEGMENTATION 3D RECONSTRUCTION 3D SHAPE RECONSTRUCTION
PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
ICCV 2019
• shunsukesaito/PIFu
•
We introduce Pixel-aligned Implicit Function (PIFu), a highly effective implicit representation that locally aligns pixels of 2D images with the global context of their corresponding 3D object.
3D HUMAN POSE ESTIMATION 3D OBJECT RECONSTRUCTION FROM A SINGLE IMAGE 3D SHAPE RECONSTRUCTION FROM A SINGLE 2D IMAGE
Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling
CVPR 2018
• xingyuansun/pix3d
• 
We study 3D shape modeling from a single image and make contributions to it in three aspects.
Ranked #1 on
3D Shape Classification
on Pix3D
3D RECONSTRUCTION 3D SHAPE MODELING 3D SHAPE RECONSTRUCTION MULTI-TASK LEARNING POSE ESTIMATION VIEWPOINT ESTIMATION
Do 2D GANs Know 3D Shape? Unsupervised 3D shape reconstruction from 2D Image GANs
ICLR 2021
• XingangPan/GAN2Shape
•
Through our investigation, we found that such a pre-trained GAN indeed contains rich 3D knowledge and thus can be used to recover 3D shape from a single 2D image in an unsupervised manner.
TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style
CVPR 2020
• chaitanya100100/TailorNet
•
While the low-frequency component is predicted from pose, shape and style parameters with an MLP, the high-frequency component is predicted with a mixture of shape-style specific pose models.
Multi-Garment Net: Learning to Dress 3D People from Images
ICCV 2019
• bharat-b7/MultiGarmentNetwork
•
We present Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL model from a few frames (1-8) of a video.
3D HUMAN POSE ESTIMATION 3D SHAPE RECONSTRUCTION FROM A SINGLE 2D IMAGE
Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion
To solve this, we propose Implicit Feature Networks (IF-Nets), which deliver continuous outputs, can handle multiple topologies, and complete shapes for missing or sparse input data retaining the nice properties of recent learned implicit functions, but critically they can also retain detail when it is present in the input data, and can reconstruct articulated humans.
3D OBJECT RECONSTRUCTION 3D RECONSTRUCTION 3D SHAPE RECONSTRUCTION
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
ECCV 2020
• facebookresearch/phosa
•
We present a method that infers spatial arrangements and shapes of humans and objects in a globally consistent 3D scene, all from a single image in-the-wild captured in an uncontrolled environment.
3D HUMAN POSE ESTIMATION 3D SHAPE RECONSTRUCTION FROM A SINGLE 2D IMAGE COMMON SENSE REASONING HUMAN-OBJECT INTERACTION DETECTION