5 accepted papers
The integration of RGB and depth modalities significantly enhances the accuracy of segmenting complex indoor scenes, with depth data from RGB-D cameras playing a crucial role in this improvement. However, collecting an RGB-D dataset is more expensive than an RGB dataset due to the need for specializ…
Monocular video depth estimation is a key challenge in computer vision, highlighting its importance in visual understanding. Monocular depth estimation models trained on single images achieve impressive results on individual frames but often lack temporal consistency when applied to videos, leading
Despite significant advances in self-supervised monocular depth estimation methods, achieving temporally consistent and accurate depth maps from frame sequences remains a formidable challenge. Existing approaches often estimate depth maps for individual frames in isolation, neglecting the rich geome
3D human pose estimation errors would propagate along the human body topology and accumulate at the end joints of limbs. Inspired by the backtracking mechanism in automatic control systems, we design an Intra-Part Constraint module that utilizes the parent nodes as the reference to build topological…
Owing to the large distribution gap between the heterogeneous data in Visible-Infrared Person Re-identification (VI Re-ID), we point out that existing paradigms often suffer from the inter-modal semantic misalignment issue and thus fail to align and compare local details properly. In this paper, we…