[OPEN][RI-IML_2019-CG-DM-HCI-008] Reconstruction of Personalized 3D Human Body Model

This internship will focus on the 3D reconstruction of the human body. Virtual body enables to generate personalized avatars which are more and more required in VR, AR, gaming and many other virtual applications. It helps increasing the embodiment and preventing from cybersickness. The intern will be included in the Immersive Lab within the Virtual Production group at Technicolor Rennes. Several tools and pieces of software developed by the team are available and will be improved. The work will consist in: (1) study the state of the art around 3D reconstruction of human avatars [1], and in particular evaluate a technique based on RGB-D video [2], (2) improve the existing camera rig and reconstruction algorithm in order to provide at the end a realistic digital double of the people.

[1] J. Achenbach, T. Waltemate, M. Erich Latoschik, and M. Botsch. 2017. Fast generation of realistic virtual humans. In Proceedings of the 23rd ACM-VRST '17
[2] Alldieck, T., Magnor, M. A., Xu, W., Theobalt, C., & Pons-Moll, G. (2018). Video Based Reconstruction of 3D People Models. arXiv preprint arXiv:1803.04758.

Skills  : Computer graphics, Python, Deep Learning, Math (optimization and geometry), English, motivated by research.

Keywords  : Geometry Processing, 3D reconstruction, deep learning

 

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

[OPEN][RI-IML_2019-CG-DM-VP-007] Deep 3D Object Localization & Tracking for Real / Virtual Fusion

 

To fuse virtual objects with real content (or the opposite) it is necessary to know the parameters of the virtual and real cameras. In particular, the 3D localization of the real camera and the real object needs to be computed and tracked to ensure temporal consistency and fast computing. Current solutions rely on visual pattern tracking. More recent technologies consider fusing information from various sensors as used for automotive applications, such as accelerometer, gyroscope, GPS, LIDAR, radar…The goal of the internship is to improve current algorithms and propose innovative solutions for filtering and fusing the various signals. Deep learning could also be considered as an improvement of existing techniques.

Skills  : Applied Mathematics, Signal Processing, Programming, Computer Vision, Machine/Deep Learning.

Keywords  : Localization, sensors, filtering, machine learning, VFX, movies.

 

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

[OPEN][RI-IML_2019-CG-HCI-005] Interactive Cage Creation for Facial Mesh Deformation

 

The purpose of the internship is to design and implement an efficient pipeline to 1/ generate automatically high-quality cages for 3D facial meshes and 2/ deform these meshes in the human face deformation space. The intern will be included in the Immersive Lab within the Virtual Production group at Technicolor Rennes. Several tools and software developed by the team are available and will be used. The work will consist in: (1) study the state of the art around cage generation and facial deformations, (2) design a pipeline to generate the cage based on any 3D facial mesh, (3) propose an approach to constrain the deformations space of the cage (4) if there is time, conduct a user study for publication.

Skills  : Computer graphics, Python, Editing/Animation tool (Blender, Maya), Maths (optimization and geometry), English, motivated by research.

Keywords  : Geometry Processing, Facial Animation, Human Interaction

 

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

[OPEN][RI-ISL_2019-CG-DM-018] Deep Geometry

3D models are often represented by very large numbers of points or triangles. This makes both storage and image synthesis inefficient, and therefore requires high-end GPUs to produce images. This internship will investigate the possibility of replacing large and detailed 3D models, normally represented as either triangle meshes or point clouds, with deep neural networks. Such networks could then be employed by a renderer to efficiently produce images.

Skills  : machine learning, 3D rendering, Python, C++.

Keywords  : .machine learning, 3D rendering, Python, C++.

 

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

RI-ISL_2019-CG-CV-VP-017

The new augmented reality devices: phones, MagicLeap… and the new 3D video standard open the door to create new AR services, making it possible to create applications that integrate real 3D animated characters in the real world. The goal of this internship is to create new experiences to evaluate and promote this kind of technologies mixing 3D video with real environments. The Star Wars holograms can now become real: “Help me. You're my only hope.”

Skills  : - Creative, enthusiast, strength of proposal - Computer Graphics / Computer Vision - Android / iOS programming - ARCore / ARKit / Unity - Ability to write well-structured and documented code - Good written and spoken English - Team working skills

Keywords  : .Augmented Reality, Point Cloud, Android programming

 

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

[OPEN][RI-ISL_2019-CG-CV-DM-020] Aging 3D Character

In VFX production (film or advertisement) the need to reconstruct 3d actor’s face from video input is increasing. Over the last decade, the technology that pulls out a 3d facial model from a flat image has been improved significantly, while fine-scale mesoscopic detail may miss out. With the recent growth of deep learning techniques, we believe that morphing a 3d character’s age would be possible, by learning “(de-)aging” from data. Done automating this pipeline brings benefits to the VFX industry, reducing manual labour. Our research team is based in Rennes & New York. And collaborates with engineers and artists located at The Mill, New York.

Skills  : Machine learning, Deep-learning, Computer Graphics, Computer Vision, Python, PyTorch, Maya.

Keywords  : .deep network, visual effects, facial rig, 3d reconstruction, shape from shading

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

[OPEN][RI-ISL_2019-CG-CV-DM-024] Extraction of quadrupeds motion parameters from video

The goal of the internship is to apply deep learning techniques for the extraction of motion parameters of quadrupeds from video. In order to cope with the lack of ground truth, the approach will build upon both weakly and unsupervised learning. Biomechanical knowledge or possibly tiny manual annotation dataset might also be exploited. The motivation for this work is to develop a statistical model of the motion of some quadrupeds in order to synthesize plausible animation.

The context of this work is the VFX workflow for animated movies industry. This work is part of an effort to automatize the currently very manual process.

The objective is to design the model and the learning methodology for extracting the 3D coordinates of a moving quadruped in video.

The expected outcome of the internship are :
- A model with the quantitative evaluation of its performance
- A description of the approach which might lead to a publication or patent
- A demo which will visually display the produced 3D animation

References
- Zhou, Xingyi, Qixing Huang, Xiao Sun, Xiangyang Xue, and Yichen Wei. "Weakly-supervised Transfer for 3D Human Pose Estimation in the Wild." arXiv preprint arXiv:1704.02447 (2017).
- Newell, Alejandro, Kaiyu Yang, and Jia Deng. "Stacked hourglass networks for human pose estimation." In European Conference on Computer Vision, pp. 483-499. Springer International Publishing, 2016.

Skills  : deep learning

Keywords  : deep learning

 

This internship is located in Rennes, France. If interested, please apply at stage.technicolor@technicolor.com  by sending us your resume and a cover letter with the internship reference in the email subject line.

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