Chapter 23 Lecture 23: Project papers and talks Monday, May 2, 2011 MIT EECS course 6.869, Bill Freeman Your final projects involve, in addition to doing the actual reading and experimentation, writing a 5-8 page paper describing your work, and presenting a short, 5 minute, talk. To help you with that, today’s lecture is about writing papers and giving talks. Since almost all of you are involved with academic research, or will be, we decided to broaden out this lecture and have it also pertain to writing papers and giving talks in general academic research, not just for this class. What makes a conference paper good will also your projects be good, and we hope the general academic advice will be useful to you. 23.1 Papers Let’s start with writing papers. First of all, when should you write a paper? You’re doing your research, making progress, when do you decide, “ok, I’d better package this up now”? I think in some ideal world, it would be entirely driven by the progress of the work itself. You get a good result, you write it up, and you submit it somewhere. But, in practice, paper submission is often driven by conference or special issue deadlines. This can be both a good and a bad thing. A conference deadline can cause people to submit something before it’s ready. On the other hand, these deadlines are great forcing functions, and lots of good work can happen in the month preceeding a conference submission deadline. In deciding when to write up research work, an important thing to note is the following (subjective) curve, showing the benefit to one’s career for publishing a paper as a function of the quality of that paper. The curve is flat (or below zero!) for almost all papers until the quality level becomes very good, and then a paper is very valuable. My point: only the good papers count. Nobody remembers boring papers, and nobody cares about them. It probably wasn’t worth the effort to write them up. Packaging up your results and writing up a paper is a lot of work, and there’s a real opportunity cost to publishing mediocre papers. You may miss out on aiming high and getting some really good result. My own experience: when I was a graduate student, I only wrote up things when I felt I had some- thing to say. I remember two conference paper submission deadlines when the lab was in a frenzy of paper-writing and I was just doing my research because I didn’t have a good result then. That turned out to be a good strategy for me. Let’s talk for a bit about where to publish papers. For the past 10 or 20 years, the “action” in computer vision is at the top conferences. That’s where the exciting new results are published and read. Journals are still useful, but they play a different role now. Now they’re used for coherent summaries of several 1
Figure 23.1: Curve showing a paper’s impact on your career as a function of its quality. conference papers, or for making archival versions of your favorite conference papers. Journal papers allow for more detail, and more perspective in an article. There are 3 top-tier conferences in computer vision: • CVPR, Computer Vision and Pattern Recognition, annual conference, always somewhere in North America, but very international in membership. • ICCV, International Conference on Computer Vision, every two years, cycles through being in North America, Europe, and Asia. • ECCV, European Conference on Computer Vision, happens every year that ICCV does not happen. All these conferences have 20-25% acceptance rates, and awards for the best papers, etc. Oftentimes computer vision research borders on computer graphics research, or machine learning, so important related conferences are: • SIGGRAPH, stands for Special Interest Group on Graphics. This is the top computer graphics conference. Since computer graphics now uses captured images and surfaces, they often publish work using computer vision or image processing techniques. • SIGGRAPH Asia, is a version of Siggraph in Asia. Almost as prestigious as Siggraph, but not quite. • NIPS, Neural Information Processing Systems. The top machine learning conference, publishes work on applications of machine learning methods to vision, or relating to the statistics of natural images. SIGGRAPH is such a high-quality publication venue that simply counting the number of Siggraph publications is a reasonably good measure of impact in graphics. The journals, Science and Nature, are also very prestigious publication venues, although computer vision work is seldom published there. The work needs to have a science component.
23.1.1 a CVPR paper Ok, so let’s assume you’re submitting it to CVPR. This is exactly the format of paper we’d like to see for your final projects, so now all the rest, regarding writing, applies equally well to your final projects as to any research project you may be submitting to CVPR. The paper can be eight or fewer pages. Here is a template for the typical organization of a paper: • Introduction • Related work • Image Model [[main idea]] • Algorithm • Experiments • Discussion These headings (and the images) are from a paper of mine. I’m not saying it’s a great paper, but it’s a well-organized paper. Introduction Now let’s examine the content, what to say within these headings. My thesis advisor, Ted Adelson, had good advice regarding writing a paper. He gave this in response to an informal survey by a graduate student. 1. Start by stating which problem you are addressing, keeping the audience in mind. They must care about it, which means that sometimes you must tell them why they should care about the problem. 2. Then state briefly what the other solutions are to the problem, and why they aren’t satisfactory. If they were satisfactory, you wouldn’t need to do the work. 3. Then explain your own solution, compare it with other solutions, and say why it’s bettter. 4. At the end, talk about related work where similar techniques and experiments have been used, but applied to a different problem. Since I developed this formula, it seems that all the papers I’ve written have been accepted. (told infor- mally, in conversation, 1990). Most of those points would be made in the introduction and related work section of the paper. Typi- cally, the Introduction tells the story using a broad brush. Sometimes the professor may write the intro- duction, since they know best how to situate the work relative to what other people have done, while the graduate student may write the rest of the paper, since they know the details of what they did. Some of my friends complain that all they write now are introductions. The reader should have the high level story in mind, after they read the introduction–the problem the paper addresses, the paper’s main contribution or insight, and a rough idea of the techniques used.
Recommend
More recommend
