Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval.

Related tags

Deep LearningDARP-SBIR
Overview

DARP-SBIR

Intro

This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval. The python files SBIR_*.py are the core framework codes to run this project under different settings, by integrating training code and evaluation code all in one file.

Dependencies

  • numpy
  • pickle
  • pytorch>=1.5.0
  • torchvision>=0.7.0
  • tqdm
  • tensorboard
  • bresenham
  • Pillow

Pre-trained

Results and Commands

Result

To produce such results, run the corresponding entrance main files.

  • Triplet Network: main_pure.py
  • Triplet + Vanilla RL: main_RL.py
  • Triplet + PPO: main_finetune.py
  • Bootstrapped DQN: main_dqn.py
  • DARP-SBIR: main_boot.py

For the other two datasets, use main_shoev2.py and main_sketchy.py

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