mlsanityData to 7 Oct 2026

INSTA-BNN: Binary Neural Network with INSTAnce-aware Threshold

arXiv 2204.07439 ↗First posted 15 Apr 2022cs.CV cs.LGcited by 9

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Abstract (arXiv)

Binary Neural Networks (BNNs) have emerged as a promising solution for reducing the memory footprint and compute costs of deep neural networks, but they suffer from quality degradation due to the lack of freedom as activations and weights are constrained to the binary values. To compensate for the accuracy drop, we propose a novel BNN design called Binary Neural Network with INSTAnce-aware threshold (INSTA-BNN), which controls the quantization threshold dynamically in an input-dependent or instance-aware manner. According to our observation, higher-order statistics can be a representative metric to estimate the characteristics of the input distribution. INSTA-BNN is designed to adjust the threshold dynamically considering various information, including higher-order statistics, but it is also optimized judiciously to realize minimal overhead on a real device. Our extensive study shows that INSTA-BNN outperforms the baseline by 3.0% and 2.8% on the ImageNet classification task with comparable computing cost, achieving 68.5% and 72.2% top-1 accuracy on ResNet-18 and MobileNetV1 based models, respectively.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 25 of its 44 references that are in the map. First posted on arXiv 15 Apr 2022.

Builds on

25 of 44 references.

References · 25

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
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  7. 2017Squeeze-and-Excitation Networkscited by 4,763
  8. 2014Going Deeper with Convolutionscited by 4,231
  9. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  10. 2013Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computationcited by 2,031
  11. 2016XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networkscited by 829
  12. 2019Learned Step Size Quantizationcited by 604
13 more
  1. 2015Learning Deconvolution Network for Semantic Segmentationcited by 365
  2. 2018Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithmcited by 233
  3. 2020ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functionscited by 183
  4. 2019Forward and Backward Information Retention for Accurate Binary Neural Networkscited by 169
  5. 2020Training Binary Neural Networks with Real-to-Binary Convolutionscited by 111
  6. 2019XNOR-Net++: Improved Binary Neural Networkscited by 94
  7. 2021ReCU: Reviving the Dead Weights in Binary Neural Networkscited by 51
  8. 2021PokeBNN: A Binary Pursuit of Lightweight Accuracycited by 48
  9. 2020High-Capacity Expert Binary Networkscited by 34
  10. 2017Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resourcescited by 23
  11. 2020BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activationscited by 23
  12. 2020Improving Accuracy of Binary Neural Networks using Unbalanced Activation Distributioncited by 15
  13. 2021Dynamic Binary Neural Network by learning channel-wise thresholdscited by 13

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 5; 2025: 3.

9 papers.

  1. 2023Temporal Dynamic Quantization for Diffusion Modelscited by 81
  2. 2024Binarized Low-light Raw Video Enhancementcited by 17
  3. 2024BinaryDM: Accurate Weight Binarization for Efficient Diffusion Modelscited by 11
  4. 2024PTQ4VM: Post-Training Quantization for Visual Mambacited by 9
  5. 2024BOLD: Boolean Logic Deep Learningcited by 3
  6. 2025ProfilingAgent: Profiling-Guided Agentic Reasoning for Adaptive Model Optimizationcited by 3
  7. 2024OvSW: Overcoming Silent Weights for Accurate Binary Neural Networkscited by 2
  8. 2025Expanding-and-Shrinking Binary Neural Networkscited by 0
  9. 2025BD-Net: Has Depth-Wise Convolution Ever Been Applied in Binary Neural Networks?cited by 0