Fall 2023 CS543/ECE549 Projects

Proposals due October 18, progress reports due November 13, final reports due December 15

• Find a previously published computer vision paper (either a recent or classic one), reimplement and test its approach. You may want to follow the spirit of the 2021 ML Reproducibility Challenge (if not necessarily consider submitting to it).
• Take some publicly available code, apply it to an interesting dataset, explore various extensions and modifications, or compare multiple approaches. Note, however, that merely running existing code on the data provided by the authors is not sufficient -- you need to do more in-depth exploration along the lines suggested above.
• Design and implement a solution to a problem that interests you. It is fine to pick a problem related to your RA or dissertation research, but be sure to formulate a clear short-term goal and desired outcome for the class project. Ideally, you should use the class project as an opportunity to try new techniques that you might not consider or have a chance to use otherwise.
• Find an interesting competition or dataset on Kaggle. It is not necessary to actually enter the competition -- just use however much of the data or problem definition or evaluation makes sense to you and is feasible in your circumstances.
• For inspiration, feel free to browse the list of project titles from the last decade of this class. However, don't feel that you need to choose a popular topic -- in particular, there is no requirement to use deep learning!

FAQ

• Can I do a project on my own? Yes, in principle, but I want to be sure this will work; check with me by email, using "SINGLETON PROJECT" in the header.
• Can I hand in the final report early? Yes
• Can I do something that I'm doing for my thesis? or for my RA work? or for another class? The principle that applies here is we must avoid double counting; you can't get two or more grades for the same piece of work. So I need to know which part of your activity counts toward CS543/ECE549 and which towards some other thing. Apart from that, great.
• What if I try really hard but it doesn't work? That's life - explain what you tried and why it didn't work (to the extent you can).
• What if I didn't try really hard and it doesn't work? You might be able to work the answer out for yourself; don't do this
• Can I use other people's code? Sure; the principle that applies here is that I need to know what you did so you should declare that you used other people's code; otherwise, have fun.
• I tried to use someone else's code but it didn't work (or I can't get it installed; or...); can you fix it? This sort of thing happens surprisingly often. Likely no, but if you try Canvas/Campuswire/TA's/your colleagues you might get lucky. Also, google it; sometimes other people have had this problem as well, and you can benefit from their experience. It's good manners and good practice to acknowledge help you received.
• I had a brilliant project idea the day before projects were due and I did that, but there wasn't enough time; what will happen to me?You might be able to work the answer out for yourself; don't do this
• I tried to use someone else's dataset, and I found something nasty; what to do? This sort of thing happens with datasets collected from the web. Consult me if absolutely essential.
• Can I work on (controversial topic X)? Sure. Try not to stir up negative publicity without a good reason. If your project requires disturbing data, don't show it to people without some warning. Be aware that there are some kinds of data you can't legally possess (classified images; images of child abuse; etc), so avoid projects that require this kind of data.

Proposal

1. List of group members.
2. Informative project title.
3. Project description and goals: Describe the problem you plan to solve and give a basic outline of what you propose to implement. You can change later as you go along, but try to think this through as much as possible in advance. Identify the desired final outcome and pose maximum and minimum goals.
4. Member roles: Indicate which project component each group member will be responsible for and how the group will interact.
5. Resources: Specify what data you plan to use -- include examples of images and any required annotations. What is your implementation platform? Do you plan to use any outside code and how do you plan to build on it? Do you have access to adequate computational resources if your project is computationally intenstive? Be specific and give pointers to all relevant resources.
6. Reservations: Try to anticipate which part of the implementation or testing may prove the most difficult. Possible stumbling blocks shouldn't necessarily prevent you from attempting a more ambitious project, but you should make sure that you have a realistic "minimum" goal that can be accomplished.
7. Relationship to your background: Describe how your proposed project relates to your background and current level of knowledge. Which techniques, software packages, etc., are you already familiar with, and which ones will be new to you? If the project is related to your dissertation or RA work, describe the relationship and the amount of overlap. It is fine to pick a problem related to your RA or dissertation research, but be sure to formulate a clear short-term goal and desired outcome for the class project. Ideally, you should use the class project as an opportunity to try new techniques that you might not consider or have a chance to use otherwise. Grading of your project will be relative to your background and the size of your team.

The proposal in PDF format should be uploaded on Canvas by one designated group member (but make sure that everybody's names are on the document). The proposal will receive feedback but no separate score. Late days will be substracted from the three-day project budget (see class policies).

Progress report

The progress report should be uploaded on Canvas by one designated group member (but make sure that everybody's names are on the document). The report will not receive a separate score, but its content and quality will contribute holistically to the overall project grade at the end of the semester.

Final report