Thermal-Det is the first LLM-supervised open-vocabulary thermal object detector, created via synthetic data conversion from GroundingCap-1M and RGB-to-thermal distillation, yielding 2-4% AP gains on benchmarks.
Kaist multi-spectral day/night data set for autonomous and assisted driving.IEEE Transactions on Intelligent Transportation Systems, 19(3):934–948
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
dataset 1
citation-polarity summary
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2roles
dataset 1polarities
use dataset 1representative citing papers
A dual-stream vision transformer with modality-aware gated exchange and bidirectional token exchange fuses RGB, thermal, and event data to improve UAV vehicle detection over dual-modal baselines on a new 10,489-frame dataset.
citing papers explorer
-
Thermal-Det: Language-Guided Cross-Modal Distillation for Open-Vocabulary Thermal Object Detection
Thermal-Det is the first LLM-supervised open-vocabulary thermal object detector, created via synthetic data conversion from GroundingCap-1M and RGB-to-thermal distillation, yielding 2-4% AP gains on benchmarks.
-
Tri-Modal Fusion Transformers for UAV-based Object Detection
A dual-stream vision transformer with modality-aware gated exchange and bidirectional token exchange fuses RGB, thermal, and event data to improve UAV vehicle detection over dual-modal baselines on a new 10,489-frame dataset.