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
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentation	Weixuan Sun, Jing Zhang, Zheyuan Liu	2021	arxiv 2112.02841
Visual Transformers with Primal Object Queries for Multi-Label Image Classification	Vacit Oguz Yazici, Joost van de Weijer, Longlong Yu	2021	arxiv 2112.05485
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization	Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina	2022	arxiv 2205.07839
BodyMap: Learning Full-Body Dense Correspondence Map	Anastasia Ianina, Nikolaos Sarafianos, Yuanlu Xu	2022	arxiv 2205.09111
iFS-RCNN: An Incremental Few-shot Instance Segmenter	Khoi Nguyen, Sinisa Todorovic	2022	arxiv 2205.15562
MoCoViT: Mobile Convolutional Vision Transformer	Hailong Ma, Xin Xia, Xing Wang	2022	arxiv 2205.12635
Pointly-Supervised Instance Segmentation	Bowen Cheng, Omkar Parkhi, Alexander Kirillov	2021	arxiv 2104.06404
Exploring Structure-aware Transformer over Interaction Proposals for Human-Object Interaction Detection	Yong Zhang, Yingwei Pan, Ting Yao	2022	arxiv 2206.06291
Multi-Scale Feature Aggregation by Cross-Scale Pixel-to-Region Relation Operation for Semantic Segmentation	Yechao Bai, Ziyuan Huang, Lyuyu Shen	2021	arxiv 2106.01744
Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing	Leonardo Rossi, Akbar Karimi, Andrea Prati