SOTA2 Research · papers

Papers for “coco”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

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20 indexed

Title	Authors	Year	Source
Adapter is All You Need for Tuning Visual Tasks	Dongshuo Yin, Leiyi Hu, Bin Li	2023	arxiv 2311.15010
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows	Ze Liu, Yutong Lin, Yue Cao	2021	arxiv 2103.14030
Patch-level Representation Learning for Self-supervised Vision Transformers	Sukmin Yun, Hankook Lee, Jaehyung Kim	2022	arxiv 2206.07990
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation	Gang Li, Xiang Li, Yujie Wang	2021	arxiv 2112.04840
Solving Travelling Thief Problems using Coordination Based Methods	Majid Namazi, M.A. Hakim Newton, Conrad Sanderson	2023	arxiv 2310.07156
5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks	Dongshuo Yin, Leiyi Hu, Bin Li	2024	arxiv 2408.08345
Detect Everything with Few Examples	Xinyu Zhang, Yuhan Liu, Yuting Wang	2023	arxiv 2309.12969
Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects	Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das	2024	arxiv 2410.01816
MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection	Kemal Oksuz, Selim Kuzucu, Tom Joy	2023	arxiv 2309.14976
PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers	Ryan Grainger, Thomas Paniagua, Xi Song	2022	arxiv 2203.11987