[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-ISL_2019-CG-CV-VP-017] Augmented Reality Point Clouds: Real Hologram Experience

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-DM-VP-015] Speeding-up video coding with deep-learning

The topic of this internship is the development of Deep Learning based methods to speed-up/improve state-of –the-art video codec (namely VCC/H.266). The goal of the internship is to tackle the combinatory problem arising with the new codecs, especially because of the enhanced block topologies available in the codec. The goal is to manage combinatory reduction without decreasing the codec performance. Deep Learning based methods have already proved their efficiency for intra coding mode (see http://phenix.int-evry.fr/jvet/doc_end_user/documents/10_San%20Diego/wg11/JVET-J0034-v2.zip). Many extensions are possible, especially regarding the inter coding mode, dealing with motion field segmentation. The candidate should be familiar with current machine learning software packages and have a good background in image processing in general.

Skills  : Skills: (deep) learning algorithms and software, programming (C++/python), motion estimation

Keywords  : video codec, machine learning, motion segmentation, image processing

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-VP-019] Exploration of Advanced video compression technologies

MPEG and VCEG are jointly exploring, in a standardization project named JVET, future video coding technologies, as successors of the AVC and HEVC video coding standards. Technicolor is deeply involved in this exploration process. The internship aims at exploring new tracks for improving video compression, mostly focused on inter prediction and coding. The research work will be made based on the reference software developed by JVET. The internship will take place in a research team of several video coding and standardization experts. It will also benefit from the Technicolor experts working on HDR and Color science

Skills  : video coding, signal and video processing, c++

Keywords  : .video coding, motion prediction, intra prediction, motion coding, intra coding, HEVC, JVET, HDR

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-CV-DM-VP-021] Deep Learning for Rotoscoping

Very recently deep learning approaches allowed developing very efficient approaches in various fields (e.g., image/video processing, computer vision, audio processing). This internship proposal targets the development of deep learning approaches for high-end visual effects. In this context, both the interaction with a user (roto artist) and the efficient propagation of the effect throughout a whole sequence are keys to achieve both a highly accurate and efficient process. The proposal will target these two aspects, interaction and spatio-temporal propagation in the context of deep learning segmentation and matting methods. Resulting algorithms might be integrated in a professional VFX software to help the colorists.

Skills  : machine learning, deep learning, computer vision, video/image processing, PyTorch, TensorFlow or Keras deep learning frameworks, Python or C++.

Keywords  : .machine learning (deep learning), video processing, computer vision, interaction, segmentation, tracking, rotoscoping, matting

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-CV-DM-VP-022] Deep learning for 3D face rig

This internship proposal targets development of deep learning approaches for high-end visual effects (generation and animation of 3D avatars for film studios). Recent techniques, such as MoFA, achieve good 3D face rig reconstruction from still images and videos. However, these face rigs only cover skin parts, missing eyes and mouth interior. To improve this, we propose to study the use of Generative Adversarial Networks (GAN) to fill these parts.

Skills  : machine learning, deep learning, computer vision, video/image processing, PyTorch, Python

Keywords  : .machine learning, deep learning, video processing, computer vision

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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