New Datasets for 3D Human Pose Estimation

8 November 2018

New Datasets for 3D Human Pose Estimation

Human pose estimation is а fundamental problem in computer vision. Computer’s ability to recognize and understand humans in images and videos is crucial for multiple tasks including autonomous driving, action…

New Datasets for 3D Object Recognition

6 November 2018

New Datasets for 3D Object Recognition

Robotics, augmented reality, autonomous driving – all these scenarios rely on recognizing 3D properties of objects from 2D images. This puts 3D object recognition as one of the central problems…

3D Hair Reconstruction Out of In-the-Wild Videos

22 October 2018
hair reconstruction from video

3D Hair Reconstruction Out of In-the-Wild Videos

3D hair reconstruction is a problem with numerous applications in different areas such as Virtual Reality, Augmented Reality, video games, medical software, etc. As a non-trivial problem, researchers have proposed…

Head Reconstruction from Internet Photos

15 October 2018
head reconstruction internet photos

Head Reconstruction from Internet Photos

Methods that reconstruct 3D models of people’s heads from images need to account for varying 3D pose, lighting, non-rigid changes due to expressions, relatively smooth surfaces of faces, ears, and…

Inferring a 3D Human Pose out of a 2D Image with FBI

16 July 2018
3D pose estimation based on 2D joints and Forward-or-Backward Information (FBI) for each bone

Inferring a 3D Human Pose out of a 2D Image with FBI

Autonomous driving, virtual reality, human-computer interaction and video surveillance — these are all application scenarios, where you would like to derive a 3D human pose out of a single RGB…

3D Hair Reconstruction Out of a Single Image

10 July 2018
3D Hair Reconstruction Out of a Single Image

3D Hair Reconstruction Out of a Single Image

Generating a realistic 3D model of an object out from 2D data represents a challenging task and this problem has been explored by many researchers in the past. The creation…

Depth Estimation Using Encoder-Decoder Networks and Self-Supervised Learning

25 June 2018
depth estimation using neural networks

Depth Estimation Using Encoder-Decoder Networks and Self-Supervised Learning

Modern autonomous mobile robots (including self-driving cars) require a strong understanding of their environment in order to operate safely and effectively. Comprehensive and accurate models of the surrounding environment are…