Scientists at The University of Texas at Austin have developed an exciting new 3D printing method that blends soft and hard materials into one seamless object.

Vision-based 3D object detection, a cost-effective alternative to LiDAR-based solutions, plays a crucial role in modern autonomous driving systems. Meanwhile, deep models have been proven susceptible ...

We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene ...

What was this cosmic discovery? ASKAP J1832-0911, the unknown space object that the global team of astronomers first spotted in December 2023, is categorized as a long-period transient.

Self-supervised deep learning models can accurately perform 3D segmentation of cell nuclei in complex biological tissues, enabling scalable analysis in settings with limited or no ground truth ...

3D object detection is a fundamental yet critical task for autonomous driving. In this paper, we investigate a novel self-distilling paradigm by proposing Self-distilling Introspective Data (SID) to ...