3 accepted papers
Generating rich and controllable motion is a pivotal challenge in video synthesis. We propose *Boximator*, a new approach for fine-grained motion control. Boximator introduces two constraint types: *hard box* and *soft box*. Users select objects in the conditional frame using hard boxes and then use…
State-of-the-art grammatical error correction (GEC) systems rely on parallel training data (ungrammatical sentences and their manually corrected counterparts), which are expensive to construct. In this paper, we employ the Break-It-Fix-It (BIFI) method to build an unsupervised GEC system. The BIFI f…
Deep neural networks are vulnerable to adversarial attacks, where a small perturbation to an input alters the model prediction. In many cases, malicious inputs intentionally crafted for one model can fool another model. In this paper, we present the first study to systematically investigate the tran…