4 accepted papers
Accurate data association is crucial in reducing confusion such as ID switches and assignment errors in multi-object tracking (MOT). However existing advanced methods often overlook the diversity among trajectories and the ambiguity and conflicts present in motion and appearance cues leading to conf…
Even with a still image, humans can ratiocinate various visual cause-and-effect descriptions before, at present, and after, as well as beyond the given image. However, it is challenging for models to achieve such task–the visual event ratiocination, owing to the limitations of time and space. To thi…
Credit card transaction fraud costs billions of dollars to card issuers every year. Besides, the credit card transaction dataset is very skewed, there are much fewer samples of frauds than legitimate transactions. Due to the data security and privacy, different banks are usually not allowed to share…
Visual reasoning between visual image and natural language description is a long-standing challenge in computer vision. While recent approaches offer a great promise by compositionality or relational computing, most of them are oppressed by the challenge of training with datasets containing only a l…