6 accepted papers
Evaluating the safety of autonomous vehicles (AVs) requires diverse, safety-critical scenarios, with collisions being especially important yet rare and unsafe to collect in the real world. Therefore, the community has been focusing on generating safety-critical scenarios in simulation. However, cont…
Traffic Atomic Activity, which describes traffic patterns for topological intersection dynamics, is a crucial topic for the advancement of intelligent driving systems. However, existing atomic activity datasets are collected from an egocentric view, which cannot support the scenarios where traffic a
Understanding a procedural activity requires modeling both how action steps transform the scene, and how evolving scene transformations can influence the sequence of action steps, even those that are accidental or erroneous. Existing work has studied procedure-aware video representations by modeling…
In this paper we study multi-label atomic activity recognition. Despite the notable progress in action recognition it is still challenging to recognize atomic activities due to a deficiency in holistic understanding of both multiple road users' motions and their contextual information. In this paper…
Intelligent driving systems aim to achieve a zero-collision mobility experience, requiring interdisciplinary efforts to enhance safety performance. This work focuses on risk identification, the process of identifying and analyzing risks stemming from dynamic traffic participants and unexpected event…
Dynamic inference that adaptively skips parts of model execution based on the complexity of input data can effectively reduce the computation cost of deep learning models during the inference. However, current architectures for dynamic inference only consider the exits at the block level, whose resu…