Update app.py

app.py

@@ -368,8 +368,8 @@ with gr.Blocks(css=".custom-label { font-weight: bold !important; font-size: 16p
     gr.Markdown(
         "<b>☉ Powered by the fine-tuned ViT models that is pre-trained from [FSFM-3C](https://fsfm-3c.github.io/)</b> <br> "
         "<b>☉ We do not and cannot access or store the data you have uploaded!</b> <br> "
-        "<b>☉ Release (Continuously updating) </b> <br> <b>[V1.0] 2025/02/22-Current🎉</b>: "
-        "1) Updated <b>[✨Unified-detector_v1] for Unified Physical-Digital Face Attack&Forgery Detection, a ViT-B/16-224 (FSFM Pre-trained) detector that could identify Real&Bonafide, Deepfake, Diffusion&AIGC, Spooing&Presentation-attacks facial images or videos </b> ; 2) Provided the selection of the number of video frames (uniformly sampling 1-32 frames, more frames may time-consuming for this page without GPU acceleration); 3) Fixed some errors of V0.1 including loading and prediction. <br>"
+        "<b>☉ Release (Continuously updating [by [Gaojian Wang/汪高健](https://scholar.google.com/citations?user=tpP4cFQAAAAJ&hl=zh-CN&oi=ao), [Tong Wu/吴桐](https://github.com/Coco-T-T), [Xingtang Luo/罗兴塘](https://github.com/Rox-C)]) </b> <br> <b>[V1.0] 2025/02/22-Current🎉</b>: "
+        "1) Updated <b>[✨Unified-detector_v1] for Physical-Digital Face Attack&Forgery Detection, a ViT-B/16-224 (FSFM Pre-trained) detector that could identify Real&Bonafide, Deepfake, Diffusion&AIGC, Spooing&Presentation-attacks facial images or videos </b> ; 2) Provided the selection of the number of video frames (uniformly sampling 1-32 frames, more frames may time-consuming for this page without GPU acceleration); 3) Fixed some errors of V0.1. <br>"
         "<b>[V0.1] 2024/12-2025/02/21</b>: "
         "Create this page with basic detectors [DfD-Checkpoint_Fine-tuned_on_FF++, FAS-Checkpoint_Fine-tuned_on_MCIO] that follow the paper implementation. <br> ")
     gr.Markdown(