Update README.md

README.md

@@ -1,3 +1,64 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- text-to-image
+language:
+- en
+tags:
+- CVPR
+---
+
+## CVPR 2021 Accepted Paper Meta Info Dataset
+
+This dataset is collect from the CVPR 2021 Open Access website (https://openaccess.thecvf.com/CVPR2021) as well as the arxiv website DeepNLP paper arxiv (http://www.deepnlp.org/content/paper/cvpr2021). For researchers who are interested in doing analysis of CVPR 2021 accepted papers and potential trends, you can use the already cleaned up json files. Each row contains the meta information of a paper in the CVPR 2021 conference. To explore more AI & Robotic papers (NIPS/ICML/ICLR/IROS/ICRA/etc) and AI equations, feel free to navigate the Equation Search Engine (http://www.deepnlp.org/search/equation) as well as the AI Agent Search Engine to find the deployed AI Apps and Agents (http://www.deepnlp.org/search/agent) in your domain. 
+
+
+Equations Latex code and Papers Search Engine
+![AI Equations and Search Portal](https://raw.githubusercontent.com/AI-Agent-Hub/AI-Agent-Marketplace/refs/heads/main/docs/equation_search_portal.jpg)
+
+
+### Meta Information of Json File of Paper
+
+```
+{
+    "title": "Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification",
+    "authors": "Haowei Zhu, Wenjing Ke, Dong Li, Ji Liu, Lu Tian, Yi Shan",
+    "abstract": "Recently, self-attention mechanisms have shown impressive performance in various NLP and CV tasks, which can help capture sequential characteristics and derive global information. In this work, we explore how to extend self-attention modules to better learn subtle feature embeddings for recognizing fine-grained objects, e.g., different bird species or person identities. To this end, we propose a dual cross-attention learning (DCAL) algorithm to coordinate with self-attention learning. First, we propose global-local cross-attention (GLCA) to enhance the interactions between global images and local high-response regions, which can help reinforce the spatial-wise discriminative clues for recognition. Second, we propose pair-wise cross-attention (PWCA) to establish the interactions between image pairs. PWCA can regularize the attention learning of an image by treating another image as distractor and will be removed during inference. We observe that DCAL can reduce misleading attentions and diffuse the attention response to discover more complementary parts for recognition. We conduct extensive evaluations on fine-grained visual categorization and object re-identification. Experiments demonstrate that DCAL performs on par with state-of-the-art methods and consistently improves multiple self-attention baselines, e.g., surpassing DeiT-Tiny and ViT-Base by 2.8% and 2.4% mAP on MSMT17, respectively.",
+    "pdf": "https://openaccess.thecvf.com/content/CVPR2022/papers/Zhu_Dual_Cross-Attention_Learning_for_Fine-Grained_Visual_Categorization_and_Object_Re-Identification_CVPR_2022_paper.pdf",
+    "supp": "https://openaccess.thecvf.com/content/CVPR2022/supplemental/Zhu_Dual_Cross-Attention_Learning_CVPR_2022_supplemental.pdf",
+    "arXiv": "http://arxiv.org/abs/2205.02151",
+    "bibtex": "https://openaccess.thecvf.com",
+    "url": "https://openaccess.thecvf.com/content/CVPR2022/html/Zhu_Dual_Cross-Attention_Learning_for_Fine-Grained_Visual_Categorization_and_Object_Re-Identification_CVPR_2022_paper.html",
+    "detail_url": "https://openaccess.thecvf.com/content/CVPR2022/html/Zhu_Dual_Cross-Attention_Learning_for_Fine-Grained_Visual_Categorization_and_Object_Re-Identification_CVPR_2022_paper.html",
+    "tags": "CVPR 2022"
+}
+```
+
+
+## Related
+
+## AI Agent Marketplace and Search
+[AI Agent Marketplace and Search](http://www.deepnlp.org/search/agent) <br>
+[Robot Search](http://www.deepnlp.org/search/robot) <br>
+[Equation and Academic search](http://www.deepnlp.org/search/equation) <br>
+[AI & Robot Comprehensive Search](http://www.deepnlp.org/search) <br>
+[AI & Robot Question](http://www.deepnlp.org/question) <br>
+[AI & Robot Community](http://www.deepnlp.org/community) <br>
+[AI Agent Marketplace Blog](http://www.deepnlp.org/blog/ai-agent-marketplace-and-search-portal-reviews-2025) <br>
+
+## AI Agent Reviews
+[AI Agent Marketplace Directory](http://www.deepnlp.org/store/ai-agent) <br>
+[Microsoft AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-microsoft-ai-agent) <br>
+[Claude AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-claude-ai-agent) <br>
+[OpenAI AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-openai-ai-agent) <br>
+[Saleforce AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-salesforce-ai-agent) <br>
+[AI Agent Builder Reviews](http://www.deepnlp.org/store/ai-agent/ai-agent-builder) <br>
+
+## AI Equation
+[List of AI Equations and Latex](http://www.deepnlp.org/equation/category/ai) <br>
+[List of Math Equations and Latex](http://www.deepnlp.org/equation/category/math) <br>
+[List of Physics Equations and Latex](http://www.deepnlp.org/equation/category/physics) <br>
+[List of Statistics Equations and Latex](http://www.deepnlp.org/equation/category/statistics) <br>
+[List of Machine Learning Equations and Latex](http://www.deepnlp.org/equation/category/machine%20learning) <br>
+
+