mlsanityData to 7 Oct 2026

ParseNet: Looking Wider to See Better

arXiv 1506.04579 ↗First posted 15 Jun 2015cs.CVcited by 176

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Abstract (arXiv)

We present a technique for adding global context to deep convolutional networks for semantic segmentation. The approach is simple, using the average feature for a layer to augment the features at each location. In addition, we study several idiosyncrasies of training, significantly increasing the performance of baseline networks (e.g. from FCN). When we add our proposed global feature, and a technique for learning normalization parameters, accuracy increases consistently even over our improved versions of the baselines. Our proposed approach, ParseNet, achieves state-of-the-art performance on SiftFlow and PASCAL-Context with small additional computational cost over baselines, and near current state-of-the-art performance on PASCAL VOC 2012 semantic segmentation with a simple approach. Code is available at https://github.com/weiliu89/caffe/tree/fcn .

Key facts. Cited by 176 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jun 2015.

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Citing papers per year: 2021: 67; 2022: 50; 2023: 37; 2024: 16; 2025: 3; 2026: 3.

176 papers.

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  1. 2021Multi-Stage Progressive Image Restorationcited by 813
  2. 2023LISA: Reasoning Segmentation via Large Language Modelcited by 770
  3. 2021Twins: Revisiting the Design of Spatial Attention in Vision Transformerscited by 565
  4. 2021Attention Mechanisms in Computer Vision: A Surveycited by 232
  5. 2021RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whiteningcited by 213
  6. 2021Camouflaged Object Segmentation with Distraction Miningcited by 151
  7. 2022ReCo: Retrieve and Co-segment for Zero-shot Transfercited by 115
  8. 2021Semi-supervised Semantic Segmentation with Directional Context-aware Consistencycited by 112
  9. 2021Bidirectional Projection Network for Cross Dimension Scene Understandingcited by 95
  10. 2022Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentationcited by 88
  11. 2021Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigationcited by 78
  12. 2021Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentationcited by 77
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  1. 2021STEP: Segmenting and Tracking Every Pixelcited by 72
  2. 2022Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentationcited by 69
  3. 2021From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Datacited by 68
  4. 2021Mining Contextual Information Beyond Image for Semantic Segmentationcited by 48
  5. 20213D-to-2D Distillation for Indoor Scene Parsingcited by 47
  6. 2021CTNet: Context-based Tandem Network for Semantic Segmentationcited by 43
  7. 2021ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentationcited by 40
  8. 2023See, Say, and Segment: Teaching LMMs to Overcome False Premisescited by 40
  9. 2022PASTA: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain Generalizationcited by 38
  10. 2021Deep Texture-Aware Features for Camouflaged Object Detectioncited by 36
  11. 2021Progressive Semantic Segmentationcited by 35
  12. 2023Semi-Supervised Semantic Segmentation via Gentle Teaching Assistantcited by 34
  13. 2021SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular imagescited by 33
  14. 2022Unbiased Subclass Regularization for Semi-Supervised Semantic Segmentationcited by 33
  15. 2023ProtoSeg: Interpretable Semantic Segmentation with Prototypical Partscited by 33
  16. 2021PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Maskcited by 31
  17. 2021All you need are a few pixels: semantic segmentation with PixelPickcited by 30
  18. 2023UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Frameworkcited by 29
  19. 2023Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matchingcited by 29
  20. 2022MGNet: Monocular Geometric Scene Understanding for Autonomous Drivingcited by 27
  21. 2023Semantic Image Segmentation: Two Decades of Researchcited by 26
  22. 2021Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-Refinementcited by 25
  23. 2022Deep Learning for Iris Recognition: A Surveycited by 25
  24. 2023Learning Probabilistic Symmetrization for Architecture Agnostic Equivariancecited by 25
  25. 2024CoReS: Orchestrating the Dance of Reasoning and Segmentationcited by 25
  26. 2023Learning Context-aware Classifier for Semantic Segmentationcited by 23
  27. 2022DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentationcited by 22
  28. 2022Style-Hallucinated Dual Consistency Learning: A Unified Framework for Visual Domain Generalizationcited by 22
  29. 2023Learnable Ophthalmology SAMcited by 21
  30. 2021Self-Supervised Pretraining for RGB-D Salient Object Detectioncited by 20
  31. 2021Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Surveycited by 19
  32. 2021Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentationcited by 18
  33. 2021FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic Segmentationcited by 17
  34. 2021Medical Image Segmentation with 3D Convolutional Neural Networks: A Surveycited by 16
  35. 2022Scratching Visual Transformer's Back with Uniform Attentioncited by 16
  36. 2021A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentationcited by 15
  37. 2022Unsupervised Segmentation in Real-World Images via Spelke Object Inferencecited by 15
  38. 2021A Unified Efficient Pyramid Transformer for Semantic Segmentationcited by 14

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