Identifying efficient and accurate optimization algorithms is a long-desired goal for the
scientific community. At present, a combination of evolutionary and deep-learning methods …

The automatic co-speech gesture generation draws much attention in computer animation.
Previous works designed network structures on individual datasets, which resulted in a lack …

Image sensors face substantial challenges when dealing with dynamic, diverse and
unpredictable scenes in open-world applications. However, the development of image …

Autonomous vehicles (AVs) are expected to transform urban parking. AVs may not require
dedicated parking spaces near their destination. Instead, AVs can drive to the optimal …

Defined traffic laws must be respected by all vehicles when driving on the road, including
self-driving vehicles without human drivers. Nevertheless, the ambiguity of human-oriented …

Sampling, generation, and evaluation of scenarios are essential steps for intelligent testing
of autonomous vehicles. Since uncertainty in driving behavior always leads to different …

Self evolution refers to the ability of a system to evolve autonomously towards a better
performance, which is a potential trend for autonomous driving systems based on self …

One of the biggest challenges in the development of learning-driven automated driving
technologies remains the handling of uncommon, rare events that may have not been …

Despite significant progress in autonomous vehicles (AVs), the development of driving
policies that ensure both the safety of AVs and traffic flow efficiency has not yet been fully …

Heavy traffic jams are difficult to predict due to the complexity of traffic dynamics.
Understanding the network dynamics of traffic bottlenecks can help avoid critical large traffic …