app

app.py

@@ -69,7 +69,7 @@ def predict(img_input):
     return blend_images(img_pil, T.ToPILImage()(preds_up))
     
 
-title = 'FOUND - unsupervised object localization'
+title = 'FOUND - unsupervised object localization \n CVPR23'
 description = 'Gradio Demo for our CVPR23 paper "Unsupervised Object Localization: Observing the Background to Discover Objects"\n \
     The app is <i>running on CPUs</i>, inference times are therefore longer than those expected on GPU (80 FPS on a V100 GPU).\n \
     Please see below for more details.'
@@ -77,10 +77,30 @@ description = 'Gradio Demo for our CVPR23 paper "Unsupervised Object Localizatio
 article = """<h1 align="center">Unsupervised Object Localization: Observing the Background to Discover Objects </h1>
     
     ## Highlights
-    - Single <b>conv 1 x 1</b> layer trained to extract information from DINO features.
+
+    - Single **conv 1 x 1** layer trained to extract information from DINO [1] features.
     - Trained only for 2 epochs on the dataset DUTS-TR.
     - Inference runs at 80 FPS on a V100 GPU.
     - No post-processing applied in results here.
+
+    <i> Images provided are taken from VOC07 [2], ECSSD [3] and DUT-OMRON [4].</i>
+
+    ## Citation
+    ```
+    @inproceedings{simeoni2023found,
+    author    = {Siméoni, Oriane and Sekkat, Chloé and Puy, Gilles and Vobecky, Antonin and Zablocki, Éloi and Pérez, Patrick},
+    title     = {Unsupervised Object Localization: Observing the Background to Discover Objects},
+    booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}},
+    year      = {2023},
+    }
+    ```
+
+    ### References
+
+    [1] M. Caron et al. Emerging properties in self-supervised vision transformers, ICCV 2021
+    [2] M. Everingham et al. The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results
+    [3] J. Shi et al. Hierarchical image saliency detection on extended CSSD, IEEE TPAMI 2016
+    [4] C. Yang et al. Saliency detection via graph-based manifold ranking, CVPR 2013
     """
 examples = ["data/examples/VOC_000030.jpg"]