====== Semestral work voting ======

{{ :courses:b3b33vir:screenshot_2019-01-10_09.19.33.png?nolink&600 |}}


====== Semestral work topics and results ======

| Supervisor | Email | Topic | Student group | Points |
| {{:courses:b3b33vir:karel_zimmermann.png?150 |http://cmp.felk.cvut.cz/~zimmerk}}    | [[http://cmp.felk.cvut.cz/~zimmerk/|Karel Zimmermann]] \\ http://cmp.felk.cvut.cz/~zimmerk \\ zimmerk@fel.cvut.cz | Dve ulohy:   \\ **KZ1:** Segmentace kondenzacni stop letadel, \\ **KZ2:** 3D detekce a lokalizace objektu \\ [[https://docs.google.com/document/d/1E78u3-Iic6d1sfz5izpMJ-EpiV5bFXA68KIfWQt7BYU/edit?usp=sharing | detail zadani ]]  | KZ1:hejlbenj, pavlisi1 \\ KZ2: zachaji1, cechjos3, minarji3 | KZ1: 3+8+30 = 41 \\ KZ2: 5+10+35 = 50 |
| {{:courses:b3b33vir:tomas_petricek.jpg?150 |http://cmp.felk.cvut.cz/~petrito1}} | Tomas Petricek \\ petrito1@cmp.felk.cvut.cz \\ http://cmp.felk.cvut.cz/~petrito1  | **TP1**: Traversability Analysis from RGB for Mobile Robot \\ **TP2**: Volumetric Reconstruction from RGB Stereo and Segmentation \\ **TP3**: 3D Object Detection \\ [[https://docs.google.com/document/d/1PXg8NiXAudyJMitunb3s9CL_qn4hq-DN5Xw5_nLxnec/edit?usp=sharing|Details]] | TP2:zakhaand seredann davidpe5 \\ TP3:Pospíchal, Turnovec, Smrčka | TP3: 3+7+30 = 40 |
| {{:courses:b3b33vir:teymur_azayev.png?150 |http://cmp.felk.cvut.cz/~azayetey}} | Teymur Azayev \\ azayetey@fel.cvut.cz \\ http://cmp.felk.cvut.cz/~azayetey| **TA1:** Robotic manipulator control. \\ Use  [[https://github.com/CMU-Perceptual-Computing-Lab/openpose|pose segmentation network]] to train a  [[http://www.willowgarage.com/pages/pr2/overview|PR2 robot]] to imitate your movements to solve tasks in a simulator [[https://docs.google.com/document/d/1qTumaFlcFpOAmWNEGV_-Odrrnct-FwZXLWFbF_HZmcQ/edit?usp=sharing|Assignment details]].  \\  **TA2:** Controlling a [[https://gym.openai.com/envs/HandManipulateBlock-v0/|shadowhand]] simulation from camera input. \\  Use [[https://www.youtube.com/watch?v=D4C1dB9UheQ|GANs]] to cross-map simulator and real images of a human hand in order to teach the system to regress joint angles from input photo images, enabling control of the simulation from a simple rgb camera. [[https://docs.google.com/document/d/1qTumaFlcFpOAmWNEGV_-Odrrnct-FwZXLWFbF_HZmcQ/edit?usp=sharing|Assignment details]] | TA1:gartnjan, doubrpa1, trzilpa1 \\ TA2:zongomil, stefkalad, hrazdja2, hanismar \\ TA3: stetkmat, sramema4, strnavo1 | TA1: 4+7+32 = 43 \\ TA2: 5+10+35 = 50 \\ TA3:4+10+32 = 46 |

| David Coufal (CAS) | david.coufal@cs.cas.cz \\ http://www.cs.cas.cz/coufal/ | Dve temata: \\ **DC1** cycle GANs (palms)  \\ **DC2** BEGAN (faces) \\ [[https://docs.google.com/document/d/109qvZ7vrxE899NLcydBr5RIRQYII_4TLEIk0DkOBS4I/edit?usp=sharing | detail zadani ]] | DC1:starutom, spacemi6, vancpetr \\ DC2: tefrfili, ungarpet| DC1: 5+10+35 = 50 \\ DC2: 4+10+35 = 49 |
| {{ :courses:b3b33vir:hurych.jpeg?nolink&150 |}} | David Hurych (Valeo) \\ david.hurych@valeo.com \\ https://cz.linkedin.com/in/david-hurych-phd-1b862b82 | **DH1:** "Everybody dance now" - GANs for advanced human pose augmentation. \\ 1. Get the code from authors or try to rewrite it. \\ 2. Get the data necessary to train it. \\ 3. Try to re-train with original as well as new data. \\ 4. Use the trained model to have fun and present. \\ links: \\ https://arxiv.org/pdf/1808.07371.pdf \\ https://carolineec.github.io/everybody_dance_now/ \\ https://www.youtube.com/watch?v=PCBTZh41Ris | DH1:zhyliyeh, uklehada, tyleondr | DH1: 1+6+25 = 32 |
| {{ :courses:b3b33vir:jasek.jpeg?nolink&150 |}} | Otakar Jasek \\ jasekota@fel.cvut.cz \\ https://scholar.google.cz/citations?user=xA8-K9cAAAAJ&hl=en | **OJ1:** Nauceni odezvy lidaru na ruznych typech objektu. \\ [[https://docs.google.com/document/d/1gxfiKQAxQVuQyOuBgyLY4yssNw1kU4tD3HoZHR2oYDI/edit?usp=sharing | detail zadani ]] | | |

| {{ :courses:b3b33vir:salansky.jpg?nolink&150 |}} | Vojta Salansky \\ salanvoj@fel.cvut.cz \\ http://cmp.felk.cvut.cz/~salanvoj/| **VS1:** Mapování a lokalizace na reálném robotu\\ Cílem semestrální práce je simultální mapování a lokalizace reálného \\ robotu (turtlebot) v neznámem prostředí (tzv. SLAM). Studenti si \\ nastudují ROS (Robot Operating System), který je hojně využívaný pro \\ ovládání robotů a zpracování sensorických dat. Využitím hloubkových \\ dat a odometrie sestaví mapu, ve které robot lokalizují. Tato \\ semestrální práce je vhodná pro studenty, kteří si chtějí vyzkoušet \\ řízení reálného robotu a přiučit se něco nového. | VS1: jaluvmar, kochmmi1, dujavjoz | VS1: 1+7+23 = 31 |
| {{ :courses:b3b33vir:hoffman.jpeg?nolink&150 |}} | Matej Hoffman \\ matej.hoffmann@fel.cvut.cz \\ https://sites.google.com/site/matejhof/ | **MH1:** 3D human pose regression \\ [[https://docs.google.com/document/d/1sWejsAPvOmH-nksRYvpEHo1SFglwxr02NbUIj_DM9M4/edit?usp=sharing | detail zadani ]] | MH1:Lukáš Rustler, Mirek Tržil, Adéla Šterberová | MH1: 5+10+35 = 50 |
| {{ :courses:b3b33vir:krajnik.jpg?nolink&150 |}} | Tomas Krajnik \\ krajnt1@fel.cvut.cz \\ http://labe.felk.cvut.cz/~tkrajnik/ | **TK1:** Learneable Feature/Object Detection for Visual Navigation of Mobile Robots: Evaluate the performance of selected feature/object detection methods on the ability of a mobile robot to perform teach-and-repeat navigation in environments which change their appearance over time. To do so, learn to use the `bearnav' navigation system (bearnav.eu), and substitute its point-feature extraction module with methods of your choosing. \\  **TK2:** Style Transfer for Visual Navigation of Mobile Robots: Use style transfer to generate 'night' images from 'day' ones and 'winter' images from 'summer' ones. Evaluate the impact of these predicted images on the robustness of mobile robot navigation, where the robot is using a map composed of these predicted images instead of a map which is obsolete. For the evaluation, use the 'bearnav' navigation framework (bearnav.eu). | TK1:rozlijak, nguyemi5, zoulamar \\ TK2:bieleluk, pechnmar, obrkmatu | TK1: 5+10+35 = 50 \\ TK2: 4+10+35 = 49 |
| {{ :courses:b3b33vir:pecka.jpg?nolink&600 |}} | Martin Pecka \\ http://cmp.felk.cvut.cz/~peckama2/ \\ peckama2@fel.cvut.cz | **MP1:** Convolutional Networks with Uncommon Data Inputs \\ [[https://docs.google.com/document/d/1fMP8ZJIPzb8a5VCskF-DogwIVziHFhZ80NPa94BYVsE/edit?usp=sharing | detail zadani]] | | |
| {{ :courses:b3b33vir:babak_mahdian.jpg?nolink&150 |http://zoi.utia.cas.cz/mahdian}}  | Babak Mahdian (UTIA) \\ http://zoi.utia.cas.cz/mahdian} \\ mahdian@utia.cas.cz | | | |