6 accepted papers
Efficient and safe navigation in cluttered environments remains a fundamental challenge for humanoid robots, particularly due to their complex dynamics and the need to process ego-centric visual observations under significant camera motion. Traditional modular navigation pipelines often suffer from
We propose MonoBox, an innovative box-supervised segmentation method constrained by monotonicity to liberate its training from the user-unfriendly box-tightness assumption. In contrast to conventional box-supervised segmentation, where the box edges must precisely touch the target boundaries, MonoBo…
With the rapid advancement of synthetic speech technology, the challenges posed by audio deepfakes have become increasingly severe. Despite notable progress in synthetic speech detection, existing algorithms exhibit limited generalization to unknown attacks. To address these challenges, we propose W…
As AI becomes more integral in our lives, the need for transparency and responsibility grows. While natural language explanations (NLEs) are vital for clarifying the reasoning behind AI decisions, evaluating them through human judgments is complex and resource-intensive due to subjectivity and the n…
Data-driven sky models have gained much attention in outdoor illumination prediction recently, showing superior performance against analytical models. However, naively compressing an outdoor panorama into a low-dimensional latent vector, as existing models have done, causes two major problems. One i…
Successful sampling on the surface of asteroids is difficult because of their weightless environment and unknown material mechanical property. This work presents an asteroid sampler based on sweeping and grinding methods to improve the success rate of sampling. The sampler uses two brushes rotating…