mlsanityData to 7 Oct 2026

BlitzNet: A Real-Time Deep Network for Scene Understanding

arXiv 1708.02813 ↗First posted 9 Aug 2017cs.CVcited by 29

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Abstract (arXiv)

Real-time scene understanding has become crucial in many applications such as autonomous driving. In this paper, we propose a deep architecture, called BlitzNet, that jointly performs object detection and semantic segmentation in one forward pass, allowing real-time computations. Besides the computational gain of having a single network to perform several tasks, we show that object detection and semantic segmentation benefit from each other in terms of accuracy. Experimental results for VOC and COCO datasets show state-of-the-art performance for object detection and segmentation among real time systems.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Aug 2017.

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Citing papers per year: 2021: 8; 2022: 10; 2023: 6; 2024: 4; 2025: 1.

29 papers.

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  1. 2021InverseForm: A Loss Function for Structured Boundary-Aware Segmentationcited by 65
  2. 2022HybridNets: End-to-End Perception Networkcited by 30
  3. 2023Scalable Video Object Segmentation with Simplified Frameworkcited by 29
  4. 2021ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic Surgerycited by 20
  5. 2021AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learningcited by 17
  6. 2022Backbones-Review: Feature Extraction Networks for Deep Learning and Deep Reinforcement Learning Approachescited by 15
  7. 2022DiSparse: Disentangled Sparsification for Multitask Model Compressioncited by 14
  8. 2022FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutionscited by 11
  9. 2023Multi-Task Consistency for Active Learningcited by 9
  10. 2021Exposing Semantic Segmentation Failures via Maximum Discrepancy Competitioncited by 7
  11. 2021Deep Joint Source-Channel Coding for Multi-Task Networkcited by 5
  12. 2021Instance-Level Task Parameters: A Robust Multi-task Weighting Frameworkcited by 4
17 more
  1. 2022Multitask Network for Joint Object Detection, Semantic Segmentation and Human Pose Estimation in Vehicle Occupancy Monitoringcited by 4
  2. 2023GraMMaR: Ground-aware Motion Model for 3D Human Motion Reconstructioncited by 4
  3. 2025Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelinescited by 4
  4. 2021Disentangling Transfer and Interference in Multi-Domain Learningcited by 3
  5. 2022Panoptic SwiftNet: Pyramidal Fusion for Real-time Panoptic Segmentationcited by 3
  6. 2021Learning Twofold Heterogeneous Multi-Task by Sharing Similar Convolution Kernel Pairscited by 2
  7. 2022A Review of Mobile Mapping Systems: From Sensors to Applicationscited by 2
  8. 2022FasterVideo: Efficient Online Joint Object Detection And Trackingcited by 1
  9. 2023Autonomous Robotic Drilling System for Mice Cranial Window Creation: An Evaluation with an Egg Modelcited by 1
  10. 2023Attacking All Tasks at Once Using Adversarial Examples in Multi-Task Learningcited by 1
  11. 2024Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglementcited by 1
  12. 2022SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Groundingcited by 0
  13. 2022An advanced YOLOv3 method for small object detectioncited by 0
  14. 2023Label Budget Allocation in Multi-Task Learningcited by 0
  15. 2024YOLO-Former: YOLO Shakes Hand With ViTcited by 0
  16. 2024Autonomous Robotic Drilling System for Mice Cranial Window Creationcited by 0
  17. 2024DMTG: One-Shot Differentiable Multi-Task Groupingcited by 0