5 papers · 1 filter
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…
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…
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…
Dream360: Diverse and Immersive Outdoor Virtual Scene Creation via Transformer-Based 360 Image Outpainting
Hao Ai, Zidong Cao, Haonan Lu +6
360 images, with a field-of-view (FoV) of 180x360, provide immersive and realistic environments for emerging virtual reality (VR) applications, such as virtual tourism, where users…