Some recent interesting work on hand tracking and pose estimation that I liked. Creating a thread 🧵
MEgATrack: Monochrome Egocentric Articulated Hand Tracking for Virtual Reality

research.fb.com/wp-content/upl…
The Phong Surface: Efficient 3D Model Fitting using Lifted Optimization

arxiv.org/abs/2007.04940
GRAB: A Dataset of Whole-Body Human Grasping of Objects

arxiv.org/abs/2008.11200
ContactPose: A Dataset of Grasps with Object Contact and Hand Pose

arxiv.org/abs/2007.09545
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild

openaccess.thecvf.com/content_CVPR_2…

Project website: arielai.com/mesh_hands/
FingerTrak Continuous 3D Hand Pose Tracking by Deep Learning Hand

HOnnotate: A method for 3D Annotation of Hand and Object Poses

arxiv.org/abs/1907.01481
HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map

openaccess.thecvf.com/content_CVPR_2…
Weakly Supervised 3D Hand Pose Estimation via Biomechanical Constraints

arxiv.org/abs/2003.09282

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More from @ankurhandos

30 Aug
Interesting SIGGRAPH courses that I liked

1. Physics-Based Differentiable Rendering - A Comprehensive Introduction

shuangz.com/courses/pbdr-c…
Understanding AR inside and out

dl.acm.org/doi/pdf/10.114…
Virtual Hands in VR: Motion Capture, Synthesis, and Perception

dl.acm.org/doi/pdf/10.114…
Read 4 tweets
19 May
GrokNet, a universal computer vision system designed for shopping is trained on **7 datasets and 83 loss functions**.

ai.facebook.com/blog/powered-b…
Also... "we adjust the batch sizes and loss weights, using more images per batch and higher loss weights for the challenging tasks. We also use weakly supervised learning to automatically generate additional training data, further improving accuracy."
progress in segmentation over the years.
Read 5 tweets
26 Mar
I have been playing with my 2D toy example of NeRF (matthewtancik.com/nerf) that implemented to understand the role of positional encoding (PE).

code: github.com/ankurhanda/ner…

left is the dataset image, middle is results with PE and right is without it. It really helps.
This is the summary of my experiment
This figure in the paper really intrigued me arxiv.org/abs/2003.08934 so I set up a very toy 2D example to understand this. The difference in the results is significant.
Read 11 tweets

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