4 accepted papers
Accurate camera–LiDAR fusion relies on precise extrinsic calibration, which fundamentally depends on establishing reliable cross-modal correspondences under potentially large misalignments. Existing learning-based methods typically project LiDAR points into depth maps for feature fusion, which disto
Multimodal Sentiment Analysis (MSA) is the task of understanding human emotions by analyzing a combination of different data sources, such as text, audio, and visual inputs. Although recent advances have improved emotion modeling across modalities, existing methods still struggle with two fundamenta
Cameras and LiDAR are essential sensors for autonomous vehicles. The fusion of camera and LiDAR data addresses the limitations of individual sensors but relies on precise extrinsic calibration. Recently, numerous end-to-end calibration methods have been proposed; however, most predict extrinsic para
Dense video captioning aims to localize events within input videos and generate concise descriptive texts for each event. Advanced end-to-end methods require both tasks to share the same intermediate features that serve as event queries, thereby enabling the mutual promotion of two tasks. However, r…