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eess.IV2026

Beyond Visibility: Real-Time Surface Accessibility Fields from Sparse LiDAR

Bradley Scott, Sam Schofield, Richard Green

Understanding which surfaces in a scene are physically accessible to a given tool is fundamental for robotic interaction, yet 3D perception systems typically stop at geometric reco…

cs.CV2026

Positioning radiata pine branches requiring pruning by drone stereo vision

Yida Lin, Bing Xue, Mengjie Zhang +2

This paper presents a stereo-vision-based system mounted on a drone for detecting and localising radiata pine branches to support autonomous pruning. The proposed pipeline comprise…

cs.CV2026

Real-Time Branch-to-Tool Distance Estimation for Autonomous UAV Pruning: Benchmarking Five DEFOM-Stereo Variants from Simulation to Jetson Deployment

Yida Lin, Bing Xue, Mengjie Zhang +2

Autonomous tree pruning with unmanned aerial vehicles (UAVs) is a safety-critical real-world task: the onboard perception system must estimate the metric distance from a cutting to…

cs.CV2026

UE5-Forest: A Photorealistic Synthetic Stereo Dataset for UAV Forestry Depth Estimation

Yida Lin, Bing Xue, Mengjie Zhang +2

Dense ground-truth disparity maps are practically unobtainable in forestry environments, where thin overlapping branches and complex canopy geometry defeat conventional depth senso…

eess.IV2026

Progressive Per-Branch Depth Optimization for DEFOM-Stereo and SAM3 Joint Analysis in UAV Forestry Applications

Yida Lin, Bing Xue, Mengjie Zhang +2

Accurate per-branch 3D reconstruction is a prerequisite for autonomous UAV-based tree pruning; however, dense disparity maps from modern stereo matchers often remain too noisy for…

cs.CV2026

Training Deep Stereo Matching Networks on Tree Branch Imagery: A Benchmark Study for Real-Time UAV Forestry Applications

Yida Lin, Bing Xue, Mengjie Zhang +2

Autonomous drone-based tree pruning needs accurate, real-time depth estimation from stereo cameras. Depth is computed from disparity maps using , so even small disparity…