mlsanityData to 7 Oct 2026

Learning Region Features for Object Detection

arXiv 1803.07066 ↗First posted 19 Mar 2018cs.CVcited by 15

Not on the map. Why?

Abstract (arXiv)

While most steps in the modern object detection methods are learnable, the region feature extraction step remains largely hand-crafted, featured by RoI pooling methods. This work proposes a general viewpoint that unifies existing region feature extraction methods and a novel method that is end-to-end learnable. The proposed method removes most heuristic choices and outperforms its RoI pooling counterparts. It moves further towards fully learnable object detection.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Mar 2018.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 10; 2022: 4; 2023: 1.

15 papers.

Sort:

By area:

  1. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  2. 2021Group-Free 3D Object Detection via Transformerscited by 215
  3. 2021Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identificationcited by 114
  4. 2021Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibrationcited by 91
  5. 2021Temporal RoI Align for Video Object Recognitioncited by 44
  6. 2021Learning Inner-Group Relations on Point Cloudscited by 29
  7. 2021Meta-Aggregator: Learning to Aggregate for 1-bit Graph Neural Networkscited by 24
  8. 2022GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNscited by 23
  9. 2021Centroid Transformers: Learning to Abstract with Attentioncited by 20
  10. 2021IAFA: Instance-aware Feature Aggregation for 3D Object Detection from a Single Imagecited by 15
  11. 2021Survey of Image Based Graph Neural Networkscited by 7
  12. 2022Automatic Relation-aware Graph Network Proliferationcited by 6
3 more
  1. 2022Spatiotemporal Transformer Attention Network for 3D Voxel Level Joint Segmentation and Motion Prediction in Point Cloudcited by 4
  2. 2022Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challengescited by 3
  3. 2023Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA) for Remote Land-use Change Detectioncited by 2