[CLOSED] [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.

[CLOSED] [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.

[CLOSED] [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.

[CLOSED] [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. Secondly, 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 to 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++.

Keywords : appearance transfer, weathercam, 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.

[CLOSED] [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.

[CLOSED] [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.

[CLOSED] [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.

[CLOSED] [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.

[CLOSED] [IML_CG_CV_033] Diminished Reality

The successful candidate will join the Augmented Reality team to focus on the real-time removal of an undesired object in a real 3D scene. We will assume that a textured 3D model of the scene is available. Both geometric and photometric spatio-temporal consistencies should be maintained. The internship will consist in the analysis of previous works related to diminished reality and video inpainting, but also to real-time blending of textures. A solution suited to our real-time needs will be specified, implemented, tested and improved. Several cases with incremental complexity will be addressed. A particular attention will be given to the dissemination aspects: presentation to the project team, demonstrator, and technical report

Skills : 3D geometry, image processing, Unity3D/C#, real-time rendering. Fluent English mandatory. Excellent communication skills and good team player

Keywords : augmented reality, inpainting, real-time rendering

 

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.

[CLOSED] [ISL_CV_VP_035] Color Constancy by Deep Learning

Color Constancy aims to estimate the color of light source in the image. Many image processing tasks such as scene understanding may benefit from Color Constancy by using the corrected object colors. The goal of this internship is to explore and propose a new framework based on convolutional neural network (CNNs) to achieve the illuminant estimation for color constancy processing. Comparison with traditional methods should be conducted through a user test

Skills : Matlab/Python/C programming, ideally with image processing expertise Ability to write well-structure and documented code Good written and spoken English Excellent team working skills as the internship forms a part of a larger project, involving many team members Ability to work independently

Keywords : Machine Learning, Deep Learning, SVM, Clustering, Color Constancy

 

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_VP_047] Transform Coding for Dynamic Point Clouds

3D point clouds have emerged as an advanced 3D representation. Compression technologies are needed to reduce the amount of data required to represent a point cloud. As a result, MPEG has recently launched a Call for Proposals on Point Cloud Compression (PCC). Block-wise transform coding has been proven to be very successful in video coding. However, as the points of a point cloud distribute irregularly in 3D space and the 3D-blocks are very often not fully occupied, tools such as discrete cosine transform (DCT) cannot be directly applied to compress point cloud. In this internship, the aim is hence to exploit new transform coding methods for irregular point clouds which can achieve both good compression performance and low complexity. This internship proposal focuses on transform coding methods for the intra and inter coding mode modules of dynamic point clouds. Furthermore, the global transform coding methods for the intra frames of dynamic point clouds will also be studied

Skills : 3D point clouds, DCT

Keywords : 3D point clouds, DCT

 

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.

[CLOSED] [ISL_CV_DM_HCI_048] Deep Learning for Gesture Recognition

Gestures are a common form of human communication. Researchers and engineers have thus naturally developed techniques to use this form of communication to interact with computers. The development of new sensors, e.g., Kinect-like sensors, and new deep learning techniques have improved significantly the performance of gesture recognition systems. Nevertheless, these techniques are still demanding in terms of computational resources, and quantity of data for training. Improvements are still needed to make these systems work in complex environment. In this internship, the goal is to explore new deep learning techniques and the use of new type of data, e.g., event-based camera, to reduce computational costs and the quantity of data for training

Skills : A good candidate will have confidence with computer vision, deep learning and the implementation of algorithms using languages such as C/C++ or Python and libraries such as Tensorflow or Theano

Keywords : gesture recognition, hand pose estimation, 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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