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sseung0703/README.md

Seunghyun Lee 👋 sseung0703

  • Welcome to my Github page. I am a Ph.D at Inha University in South Korea.
    My research areas are machine learning, deep learning, and especially the light-weighting the convolutional neural networks such as knowledge distillation and filter pruning.
    You can find my curriculum vitae here.

ML libraries 🧱

  • Tensorflow (1.x and 2.x): Professional
  • Pytorch: Upper intermediate
  • JAX: Upper intermediate

Anurag's github stats

Academic activity 🕹

  • Google developers experts from May 2022
  • Leader of deep learning paper study group: link
  • Major contributor of the implementation project for Putting NeRF on a Diet in 🤗HuggingFace X GoogleAI Flax/JAX Community Week Event (won the 2nd price! 😆)
  • Have served as a reviewer for CVPR, ICCV, ECCV, and so on.

Publication 📜

First author of

  • "Fast Filter Pruning via Coarse-to-Fine Neural Architecture Search and Contrastive Knowledge Transfer" on IEEE TNNLS (2023) [paper]
  • "Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning" on ECCV2022 [paper] [code]
  • "Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural Network" on AAAI2021 [paper] [code]
  • "Knowledge Transfer via Decomposing Essential Information in Convolutional Neural Networks" on IEEE TNNLS (2020) [paper] [TF1 code, TF2 code]
  • "Filter Pruning and Re-Initialization via Latent Space Clustering" on IEEE Access (2020) [paper]
  • "Transformation of Non-Euclidean Space to Euclidean Space for Efficient Learning of Singular Vectors" on IEEE Access (2020) [paper]
  • "Graph-based Knowledge Distillation by Multi-head Attention Network." on BMVC2019 oral [paper] [code]
  • "Self-supervised Knowledge Distillation Using Singular Value Decomposition" on ECCV2018 [paper] [TF1 code, TF2 code]

Co-author of

  • "CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization" on IEEE Access (2022) [paper] [code]
  • "Balanced knowledge distillation for one-stage object detector" on Neurocomputing (2022) [paper]
  • "Vision Transformer for Small-Size Datasets" on arxiv preprint [paper] [code]
  • "Contextual Gradient Scaling for Few-Shot Learning" on WACV2022 [paper] [code]
  • "Zero-Shot Knowledge Distillation Using Label-Free Adversarial Perturbation With Taylor Approximation" on IEEE Access (2021) [paper] [code]
  • "Channel Pruning Via Gradient Of Mutual Information For Light-Weight Convolutional Neural Networks" on ICIP 2020 [paper]
  • "Real-time purchase behavior recognition system based on deep learning-based object detection and tracking for an unmanned product cabinet" on ESWA (2020) [paper]
  • "Metric-Based Regularization and Temporal Ensemble for Multi-Task Learning using Heterogeneous Unsupervised Tasks" on ICCVW2019 [paper]
  • "MUNet: macro unit-based convolutional neural network for mobile devices" on CVPRW2018 [paper]

and so on 🎓

Pinned Loading

  1. KD_methods_with_TF KD_methods_with_TF Public

    Knowledge distillation methods implemented with Tensorflow (now there are 11 (+1) methods, and will be added more.)

    Python 266 61

  2. Knowledge_distillation_via_TF2.0 Knowledge_distillation_via_TF2.0 Public

    The codes for recent knowledge distillation algorithms and benchmark results via TF2.0 low-level API

    Python 110 31

  3. codestella/putting-nerf-on-a-diet codestella/putting-nerf-on-a-diet Public

    Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation

    Python 267 21

  4. Zero-shot_Knowledge_Distillation Zero-shot_Knowledge_Distillation Public

    Zero-Shot Knowledge Distillation in Deep Networks in ICML2019

    Python 49 9

  5. SSKD_SVD SSKD_SVD Public

    Python 50 10

  6. EKG EKG Public

    Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning

    Python 17 1