7 papers · 1 filter
Articulation in Motion: Prior-free Part Mobility Analysis for Articulated Objects By Dynamic-Static Disentanglement
Hao Ai, Wenjie Chang, Jianbo Jiao +2
Articulated objects are ubiquitous in daily life. Our goal is to achieve a high-quality reconstruction, segmentation of independent moving parts, and analysis of articulation. Rece…
PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation
Zidong Cao, Jinjing Zhu, Weiming Zhang +4
Recently, Depth Anything Models (DAMs) - a type of depth foundation models - have demonstrated impressive zero-shot capabilities across diverse perspective images. Despite its succ…
A Survey of Representation Learning, Optimization Strategies, and Applications for Omnidirectional Vision
Hao Ai, Zidong Cao, Lin Wang
Omnidirectional image (ODI) data is captured with a field-of-view of 360x180, which is much wider than the pinhole cameras and captures richer surrounding environment details than…
CUBE360: Learning Cubic Field Representation for Monocular 360 Depth Estimation for Virtual Reality
Wenjie Chang, Hao Ai, Tianzhu Zhang +1
Panoramic images provide comprehensive scene information and are suitable for VR applications. Obtaining corresponding depth maps is essential for achieving immersive and interacti…
Elite360M: Efficient 360 Multi-task Learning via Bi-projection Fusion and Cross-task Collaboration
Hao Ai, Lin Wang
360 cameras capture the entire surrounding environment with a large FoV, exhibiting comprehensive visual information to directly infer the 3D structures, e.g., depth and surface no…
Elite360D: Towards Efficient 360 Depth Estimation via Semantic- and Distance-Aware Bi-Projection Fusion
Hao Ai, Lin Wang
360 depth estimation has recently received great attention for 3D reconstruction owing to its omnidirectional field of view (FoV). Recent approaches are predominantly focused on cr…