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Zidong Cao

9 accepted papers

2026

SkyEvents: A Large-Scale Event-enhanced UAV Dataset for Robust 3D Scene Reconstruction

ICLR 2026poster

Recent advances in large-scale 3D scene reconstruction using unmanned aerial vehicles (UAVs) have spurred increasing interest in neural rendering techniques. However, existing approaches with conventional cameras struggle to capture consistent multi-view images of scenes, particularly in extremely b…

Cited by 0SourcecodeScholar
2025

Depth Any Event Stream: Enhancing Event-based Monocular Depth Estimation via Dense-to-Sparse Distillation

ICCV 2025poster

With the superior sensitivity of event cameras to high-speed motion and extreme lighting conditions, event-based monocular depth estimation has gained popularity to predict structural information about surrounding scenes in challenging environments. However, the scarcity of labeled event data constr…

Cited by 0SourcePDFScholar
2025

PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation

CVPR 2025poster

Recently, Depth Anything Models (DAMs) - a type of depth foundation models - have demonstrated impressive zero-shot capabilities across diverse perspective images. Despite its success, it remains an open question regarding DAMs' performance on panorama images that enjoy a large field-of-view (180x36…

Cited by 0SourcePDFScholar
2025

ST$^2$360D: Spatial-to-Temporal Consistency for Training-free 360 Monocular Depth Estimation

NeurIPS 2025poster

360-degree monocular depth estimation plays a crucial role in scene understanding owing to its 180-degree by 360-degree field-of-view (FoV). To mitigate the distortions brought by equirectangular projection, existing methods typically divide 360-degree images into distortion-less perspective patches…

Cited by 0SourceScholar
2024

SRFNet: Monocular Depth Estimation with Fine-grained Structure via Spatial Reliability-oriented Fusion of Frames and Events

ICRA 2024poster

Monocular depth estimation is a crucial task to measure distance relative to a camera, which is important for applications, such as robot navigation and self-driving. Traditional frame-based methods suffer from performance drops due to the limited dynamic range and motion blur. Therefore, recent wor…

Cited by 8SourcecodeScholar
2023

Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation

CVPR 2023poster

The ability of scene understanding has sparked active research for panoramic image semantic segmentation. However, the performance is hampered by distortion of the equirectangular projection (ERP) and a lack of pixel-wise annotations. For this reason, some works treat the ERP and pinhole images equa…

Cited by 36SourcePDFScholar
2023

HRDFuse: Monocular 360deg Depth Estimation by Collaboratively Learning Holistic-With-Regional Depth Distributions

CVPR 2023poster

Depth estimation from a monocular 360 image is a burgeoning problem owing to its holistic sensing of a scene. Recently, some methods, e.g., OmniFusion, have applied the tangent projection (TP) to represent a 360 image and predicted depth values via patch-wise regressions, which are merged to get a d…

Cited by 32SourcePDFScholar
2023

OmniZoomer: Learning to Move and Zoom in on Sphere at High-Resolution

ICCV 2023poster

Omnidirectional images (ODIs) have become increasingly popular, as their large field-of-view (FoV) can offer viewers the chance to freely choose the view directions in immersive environments such as virtual reality. The Mobius transformation is typically employed to further provide the opportunity f…

Cited by 9PDFcodeScholar