3 papers
cs.CV2026
ReVMap: Vectorized Global Mapping via Connectivity-Aware Local Map Fusion
Hongjae Shin, Jungho Kim, Donghyuk Kwak +4
Large-scale annotation of vectorized high-definition (HD) maps is labor-intensive and costly, motivating local-to-global auto-labeling approaches that incrementally construct globa…
cs.RO2026
Odyssey: A Closed-Loop Benchmark for Long-Horizon Real-World Driving with Explicit Navigation Routes
Jungho Kim, Hongjae Shin, Seunghoon Yu +11
Closed-loop evaluation of end-to-end driving requires continuous rollouts that reveal how earlier decisions affect subsequent driving. However, existing benchmarks evaluate only sh…
cs.CV2026
SafeDrive: Fine-Grained Safety Reasoning for End-to-End Driving in a Sparse World
Jungho Kim, Jiyong Oh, Seunghoon Yu +3
The end-to-end (E2E) paradigm, which maps sensor inputs directly to driving decisions, has recently attracted significant attention due to its unified modeling capability and scala…