Research map / Detection and segmentation / CNN features
Searching Parameterized AP Loss for Object Detection
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Towards Accurate One-Stage Object Detection With AP-Loss (CVPR 2019 · similarity 0.90)
- Revisiting AP Loss for Dense Object Detection: Adaptive Ranking Pair Selection (CVPR 2022 · similarity 0.89)
- Correlation Loss: Enforcing Correlation between Classification and Localization (AAAI 2023 · similarity 0.87)
- Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection (NeurIPS 2020 · similarity 0.87)
- A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection (NeurIPS 2020 · similarity 0.87)
- Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search (ICLR 2021 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.