[OPEN] [IML_CV_DM_021] 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 need 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] [ISL_CV_DM_VP_022] Framework for Deep Learning Inference 

Deep learning approach enable very efficient signal processing and pattern recognition tasks in several fields including image segmentation or 3D modelling. Many frameworks are available for designing and training deep model. But the deployment of deep based inference solution in professional environments is still difficult because of many integration constraints (eg GPU, interactivity, resource sharing and complexity of DL libraries). The goal of this internship is to develop a library and a workflow for transferring, converting and using deep models into final VFX production environments. A possible use case is the interactive object segmentation

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

Keywords : machine learning (deep learning), video processing, computer vision, segmentation

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] [ISL_CV_DM_VP_023] Deep learning for rotoscoping task 

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 development of deep learning approaches for high-end visual effects. The approaches may address problems such as image segmentation, rotoscoping, matting, despilling and tracking; and 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, 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] [ISL_CG_CV_DM_027] Weather Reassignment 

In many places throughout the world weathercams are installed. Each camera creates timelapse photography of an environment over different times of day, atmospheric conditions, and seasons. This data could be leveraged to train models, enabling detection of different types of weather and time of day. Second, neural networks could be trained using this data to then apply new atmospheric conditions, weather conditions, seasonal change etc., to new images. The purpose of this research would be understand if such image transformations are possible, and to develop tools to perform such transformations. Eventually, the aim is to support our special effects businesses with new tools to carry out high level image and video edits

Skills : machine learning, 3d animation, 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.

[OPEN] [ISL_CV_DM_028] Weakly supervised quadruped modelling from video  

The goal of this internship is to develop a novel weakly supervised deep learning approach to extraction quadrupeds’ motion parameters from unconstrained videos. The motivation for this work is to build novel probabilistic models of the motion for several classes of quadrupeds. Applications include synthetic animation as well as video analysis and retargeting

Skills : machine learning, Python/C++, GPU

Keywords : deep learning, optimization, CV/CG

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] [ISL_CV_DM_029] Self-supervised deep solvers for optimization-based image manipulation 

In different domains, deep convolutional networks trained with self-supervisions have appeared as a powerful alternative to classic solvers. They allow fast runtime, circumvent initialization issues and, might yield better results in certain regimes. This internship aims at developing further this promising type of approach in the specific context of photo-realistic example-based image manipulation

Skills : machine learning, Python/C++, GPU

Keywords : deep learning, optimization, image editing

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] [ISL_CV_DM_030] Wasserstein embedding learning for animation data 

Defining relevant metric between animation data is crucial for many applications. For that purpose, Wasserstein distances are a better, but more complex, alternative to Euclidian ones. We propose in this internship to learn deep embeddings where the Euclidian distance in the output space mimics the Wasserstein one in the original space of animation data

Skills : machine learning, Python/C++, GPU

Keywords : deep learning, optimization, CV/CG

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] [IML_CV_DM_031] Deep Learning for Light-Fields 

Deep learning has already shown a big potential in many computer vision tasks. In particular it has been shown recently that depth estimation and new view synthesis for Light-Fields are two highly related problems that can be solved with deep learning techniques. However, those algorithms have only been tested on a type of Light-Field capturing devices (plenoptic cameras) having a very small parallax. In this context, this internship aims at further developing these promising approaches to other Light-Field data such as multi-camera datasets. The internship will consist in studying the state-of-the-art in deep-learning for depth-estimation and view synthesis, the implementation of a deep-learning solution specially tailored for Light-Fields and the training, validation and testing on different datasets

Skills : Machine learning, Computer vision, Python

Keywords : Deep learning, Light-Fields, Depth estimation, View synthesis

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.