Section outline

  • The first part of the evaluation will be based on paper reading & comparison, and take place on October 16th, 2023, during the course session.

    Each group of 3 students will present and compare two research papers either trying to solve the same challenge with two different strategies, or being the continuation of one another.  All of you should read the two papers carefully and meet online to discuss your understanding of the methods, and the pros and cons of each approach. You will then prepare a 10 minutes presentation (10 slides max) which should include:

    • A brief presentation of main contribution of each paper : input, output of the method, and key insight to solve the problem: Try to extract the main novel idea or novel technical method, something future work could inspire from.
    • A joint discussion of the two papers: similarities and differences, advantages/drawback of each method, application cases where each approach would be best suited.

    The slides describing the suggested choices for pairs of papers are attached.
    Once you have formed a group and made a choice among the topics still available in the list below, please email the professor, to indicate your choice: 
    1 Expressive design of kinematic animations. Alexandra Pilipyuk, Pedro Andrade Ferreira Sobrinho, Andrei Ostanin, Zhaoyang Chen2
    3
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    5 How far should we use anatomy? Muscle-based motion control. Aude Bouillé, Julien Jampsin, Benjamin Moreau. 
    6 Deep learning for motion control. Mathieu Gierski, Maximilien Bohm et Hanna Mergui
    7 Learning how to fly. Haiyang JIANG , Jackson SUNNY, Pierre OLLEON 
    8 Should we learn human gaits by imitation or discover new motion? Jingnan CAO , Ranyu FAN, and Wenqing QU.
    9
    10 Handling interactions with the scene. Ghislain Kengne Gumete, Yi-Hsuan Lee, Barthélemy Paléologue.
    11 Learning style and combining motions? Combining Deep RL with Adversarial networks. Célia Nouri, Ribal Teeny, Victor Barberteguy.