From 5d70688a7dbcf434781d74b15a00d98d0a4aa8cc Mon Sep 17 00:00:00 2001
From: Zheyuan Wu <60459821+Trance-0@users.noreply.github.com>
Date: Thu, 23 Oct 2025 14:32:35 -0500
Subject: [PATCH] Update CSE5519_J3.md

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 # CSE5519 Advances in Computer Vision (Topic J: 2023 - 2024: Open-Vocabulary Object Detection)
 
+## Grounding DINO
+
+[link to the paper](https://arxiv.org/pdf/2303.05499)
+
+### Novelty in Grounding DINO
+
+- Use CLIP to enhance the feature with DETER
+
+1. Contrastive loss for text-region alignment
+2. Localization loss-box regression (DINO style)
+3. Auxiliary loss across decoder layers
+
+Top 900 bounding boxes for inference.
+
+> [!TIP]
+>
+> This paper shows a novel approach to open-vocabulary object detection by marrying DINO with CLIP. The authors use a DINO model to get the query features and then use a grounding head to get the bounding box and class label.
+>
+> I'm really interested in the number of bounding boxes for inference. I wonder how fine-grained the bounding boxes are? Does it serve a good reference for counting problems and doing logical reasoning for example the hand with 6 fingers?
+