Seeing Heat with Color -- RGB-Only Wildfire Temperature Inference from SAM-Guided Multimodal Distillation using Radiometric Ground Truth

This meant that the student network was predicting highly accurate for some burn locations, but not as accurate for others. Some images in burns such as Willamette V alley are more consistent and have a higher temporal resolution than the Sycan Marsh burn. Additionally, some imagery in FLAME 3 contains views of smoke and trees only, and no visible fire in the image. With a three-channel RGB color image only as input, and no distinct fire colors in the image, it may have proven difficult for the student network to segment the fire region. Some of these difficulties are visualized in Figure 3, rows b - e, reflecting not necessarily poor, but not ideal results. In summary, the overall sporadic nature and no visible flames of some of the burn imagery most likely caused lower quantitative IoU for the fire region (Class 1). Sample visual results for a test image from Willamette V alley for the teachers with DeepLabV3+ student network are shown in Figure 4. Table IV shows testing results with different teacher-student variants of the temperature predictions for the ground truth fire region pixels only.