Figure5

Figure 5. Colorized images using different image colorization methods on KAIST. (A) TIR images; (B) CycleGAN^[33]; (C) Pix2pix^[23]; (D) SCGAN^[29]; (E) TIC-CGAN^[28]; (F) PealGAN^[32]; (G) MUGAN^[30]; (H) LKAT-GAN^[31]; (I) CMMF-Net; (J) True RGB images. The original infrared images (A) and RGB images (J) were obtained from https://soonminhwang.github.io/rgbt-ped-detection/data/, while the other images were reproduced using methods from other papers and generated with our laboratory's equipment. The specific methods can be found in the corresponding references listed in the bibliography. KAIST: A multispectral pedestrian dataset, proposed by the Korea Advanced Institute of Science and Technology; TIR: thermal infrared; SCGAN: saliency map-guided colorization with generative adversarial network; TIC-CGAN: thermal infrared colorization via conditional generative adversarial network; MUGAN: thermal infrared image colorization using xixed-skipping UNet and generative adversarial network; LKAT-GAN: a GAN for thermal infrared image colorization based on large kernel and attentionUNet-transformer; CMMF-Net: a generative network based on clip-guided multi-modal feature fusion for thermal infrared image colorization.