CLIP language prompts guide a new weighted cross-entropy loss (CLIP-CE via AME and FAME) to boost object detection performance in hazy images, outperforming image enhancement baselines on the introduced HazyCOCO dataset.
Dsnet: Joint semantic learning for object detection in inclement weather conditions,
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Language Prompt vs. Image Enhancement: Boosting Object Detection With CLIP in Hazy Environments
CLIP language prompts guide a new weighted cross-entropy loss (CLIP-CE via AME and FAME) to boost object detection performance in hazy images, outperforming image enhancement baselines on the introduced HazyCOCO dataset.