3 accepted papers
"Object detection is an important task that finds its application in a wide range of scenarios. Generally, it requires extensive labels for training, which is quite time-consuming, especially in crowded scenes. Recently, Segment Anything Model (SAM) has emerged as a powerful zero-shot segmenter, off…
"Recent advancements in multi-modal pre-training for 3D point clouds have demonstrated promising results by aligning heterogeneous features across 3D shapes and their corresponding 2D images and language descriptions. However, current straightforward solutions often overlook intricate structural rel…
"In this paper, we introduce PredBench, a benchmark tailored for the holistic evaluation of spatio-temporal prediction networks. Despite significant progress in this field, there remains a lack of a standardized framework for a detailed and comparative analysis of various prediction network architec…