3 accepted papers
Legged robots are supposed to traverse complicated environments, which makes it challenging to design a model-based controller due to their functional complexity. Currently, using deep reinforcement learning to improve the adaptability of robots in complex scenarios has been a major research trend.
This paper investigates the Neural Tangent Kernel (NTK) to search vision transformers without training. In contrast with the previous observation that NTK-based metrics can effectively predict CNN’s performance at initialization, we empirically show their inefficacy in the ViT search space. We hypot…
Despite the prominent success of general object detection, the performance and efficiency of Small Object Detection (SOD) are still unsatisfactory. Unlike existing works that struggle to balance the trade-off between inference speed and SOD performance, in this paper, we propose a novel Scale-aware…