Short papers at vision conferences

Recently, John Langford wrote about complexity illness on his blog. He raised concerns about the growing bias for long and dense papers in machine learning. This observation is not novel in any sense, nevertheless, it is a serious concern. Computer vision is one of the worst affected fields by this phenomenon.

The number of submissions at CVPR, ICCV, and ECCV is way too high to project a honest reflection of the state of research. I am reviewing a couple of these. Most of the papers take up the maximum permitted space, i.e., eight pages, when the recommended number of pages is six. Some of these papers present incremental approaches. These papers often provide interesting insights into a particular problem or domain, but not enough to be accepted for publication (in my opinion). It would be much better if there is an option for short papers at the vision conferences.

Short papers are encouraged in conferences in various disciplines of computer science such as information retrieval, computational linguistics, and networks (I believe). These papers provide the authors an opportunity to present their research and achievements in a concise fashion, along with a judgment about their own work. These (short) papers would not be competing with the full papers (possibly talks) for acceptance. Moreover, the authors would not have to spend any effort to "prepare" the paper to counter the prevailing complexity bias.

Such categorization of papers, as full papers and short papers, may also help alleviate the reviewing situation. Currently, each reviewer is assigned more than ten papers for each of these vision conferences. It is becoming harder to spend enough time on all of these papers for helpful, constructive, and appropriate reviews, especially when many of these papers are filling in the entire space with unnecessary details and uninteresting diversions. An alternative of short papers would provide a mechanism for the authors to be more responsible to the community, and thus make these conferences more reflective of the true state of research in computer vision.