6 accepted papers
Despite recent progress in 3D visual grounding, existing methods still struggle with three core challenges: 1) cross-modal misalignment that prevents textual cues from being reliably delivered to visual representations, 2) intra-class confusion arising from insufficient understanding of fine-grained
Recently, 3D multi-object tracking (MOT) has widely adopted the standard tracking-by-detection paradigm, which solves the association problem between detections and tracks. Many tracking-by-detection approaches establish constrained relationships between detections and tracks using a distance thresh…
Existing view transformations in vision-centric 3D Semantic Scene Completion (SSC) inevitably experience erroneous feature duplication in the reconstructed voxel space due to occlusions, leading to a dilution of informative contexts. Furthermore, semantic classes exhibit high variability in their ap…
3D traffic scene comprises various 3D information about car objects, including their pose and shape. However, most recent studies pay relatively less attention to reconstructing detailed shapes. Furthermore, most of them treat each 3D object as an independent one, resulting in losses of relative con…
Recent graph-based face clustering methods predict the connectivity of enormous edges, including false positive edges that link nodes with different classes. However, those false positive edges, which connect negative node pairs, have the risk of integration of different clusters when their connecti…
Images captured with irregular exposures inevitably present unsatisfactory visual effects, such as distorted hue and color tone. However, most recent studies mainly focus on underexposure correction, which limits their applicability to real-world scenarios where exposure levels vary. Furthermore, so…