HIVE: Evaluating the Human Interpretability of Visual Explanations

Related tags

Deep LearningHIVE
Overview

HIVE: Evaluating the Human Interpretability of Visual Explanations

Project Page | Paper

This repo provides the code for HIVE, a human evaluation framework for interpretability methods in computer vision.

@article{kim2021hive,
  author = {Sunnie S. Y. Kim and Nicole Meister and Vikram V. Ramaswamy and Ruth Fong and Olga Russakovsky},
  title = {{HIVE}: Evaluating the Human Interpretability of Visual Explanations},
  journal = {CoRR},
  volume = {abs/2112.03184},
  year = {2021}
}

Our study UIs

Distinction task

  • combined_gradcam_nolabels.html
  • combined_bagnet_nolabels.html
  • combined_protopnet_distinction.html
  • combined_prototree_distinction.html

Agreement task

  • combined_protopnet_agreement.html
  • combined_prototree_agreement.html

Additional studies

  • combined_gradcam_labels.html
  • combined_bagnet_labels.html
  • combined_prototree_agreement_tree.html

Running human studies

We ran our studies through Human Intelligence Tasks (HITs) deployed on Amazon Mechanical Turk (AMT). We use simple-amt, a microframework for working with AMT. Here we describe which files correspond to which study UIs and provide brief instructions for running studies.

Brief instructions on how to run user studies on AMT

Please check out the original simple-amt repository for more information on how to run a HIT on AMT.

Launch HITs on AMT

python launch_hits.py \
--html_template=hit_templates/combined_prototree_distinction.html \
--hit_properties_file=hit_properties/properties.json \
--input_json_file=examples/input_prototree_distinction.txt \
--hit_ids_file=examples/hit_ids_prototree_distinction.txt --prod

Check HIT progress

python show_hit_progress.py \
--hit_ids_file=examples/hit_ids_prototree_distinction.txt --prod

Get results

python get_results.py \
  --hit_ids_file=examples/hit_ids_prototree_distinction.txt \
  --output_file=examples/results_prototree_distinction.txt \
  > examples/results_prototree_distinction.txt --prod

Approve work

python approve_hits.py \
--hit_ids_file=examples/hit_ids_prototree_distinction.txt --prod
Owner
Princeton Visual AI Lab
Princeton Visual AI Lab
Tensorflow 2.x implementation of Vision-Transformer model

Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT

Soumik Rakshit 16 Jul 20, 2022
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)

Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network

21 Nov 09, 2022
PyTorch implementation of the wavelet analysis from Torrence & Compo

Continuous Wavelet Transforms in PyTorch This is a PyTorch implementation for the wavelet analysis outlined in Torrence and Compo (BAMS, 1998). The co

Tom Runia 262 Dec 21, 2022
The source code of the paper "SHGNN: Structure-Aware Heterogeneous Graph Neural Network"

SHGNN: Structure-Aware Heterogeneous Graph Neural Network The source code and dataset of the paper: SHGNN: Structure-Aware Heterogeneous Graph Neural

Wentao Xu 7 Nov 13, 2022
On-device wake word detection powered by deep learning.

Porcupine Made in Vancouver, Canada by Picovoice Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening

Picovoice 2.8k Dec 29, 2022
Airborne Optical Sectioning (AOS) is a wide synthetic-aperture imaging technique

AOS: Airborne Optical Sectioning Airborne Optical Sectioning (AOS) is a wide synthetic-aperture imaging technique that employs manned or unmanned airc

JKU Linz, Institute of Computer Graphics 39 Dec 09, 2022
A CROSS-MODAL FUSION NETWORK BASED ON SELF-ATTENTION AND RESIDUAL STRUCTURE FOR MULTIMODAL EMOTION RECOGNITION

CFN-SR A CROSS-MODAL FUSION NETWORK BASED ON SELF-ATTENTION AND RESIDUAL STRUCTURE FOR MULTIMODAL EMOTION RECOGNITION The audio-video based multimodal

skeleton 15 Sep 26, 2022
Single-stage Keypoint-based Category-level Object Pose Estimation from an RGB Image

CenterPose Overview This repository is the official implementation of the paper "Single-stage Keypoint-based Category-level Object Pose Estimation fro

NVIDIA Research Projects 188 Dec 27, 2022
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.

Swin Transformer for Semantic Segmentation of satellite images This repo contains the supported code and configuration files to reproduce semantic seg

23 Oct 10, 2022
MNIST, but with Bezier curves instead of pixels

bezier-mnist This is a work-in-progress vector version of the MNIST dataset. Samples Here are some samples from the training set. Note that, while the

Alex Nichol 15 Jan 16, 2022
Shape Matching of Real 3D Object Data to Synthetic 3D CADs (3DV project @ ETHZ)

Real2CAD-3DV Shape Matching of Real 3D Object Data to Synthetic 3D CADs (3DV project @ ETHZ) Group Member: Yue Pan, Yuanwen Yue, Bingxin Ke, Yujie He

24 Jun 22, 2022
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

Yuki M. Asano 249 Dec 22, 2022
SciFive: a text-text transformer model for biomedical literature

SciFive SciFive provided a Text-Text framework for biomedical language and natural language in NLP. Under the T5's framework and desrbibed in the pape

Long Phan 54 Dec 24, 2022
MEND: Model Editing Networks using Gradient Decomposition

MEND: Model Editing Networks using Gradient Decomposition Setup Environment This codebase uses Python 3.7.9. Other versions may work as well. Create a

Eric Mitchell 141 Dec 02, 2022
dataset for ECCV 2020 "Motion Capture from Internet Videos"

Motion Capture from Internet Videos Motion Capture from Internet Videos Junting Dong*, Qing Shuai*, Yuanqing Zhang, Xian Liu, Xiaowei Zhou, Hujun Bao

ZJU3DV 98 Dec 07, 2022
COVID-Net Open Source Initiative

The COVID-Net models provided here are intended to be used as reference models that can be built upon and enhanced as new data becomes available

Linda Wang 1.1k Dec 26, 2022
[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

CC 4.4k Dec 27, 2022
App customer segmentation cohort rfm clustering

CUSTOMER SEGMENTATION COHORT RFM CLUSTERING TỔNG QUAN VỀ HỆ THỐNG DỮ LIỆU Nên chuyển qua theme màu dark thì sẽ nhìn đẹp hơn https://customer-segmentat

hieulmsc 3 Dec 18, 2021
The NEOSSat is a dual-mission microsatellite designed to detect potentially hazardous Earth-orbit-crossing asteroids and track objects that reside in deep space

The NEOSSat is a dual-mission microsatellite designed to detect potentially hazardous Earth-orbit-crossing asteroids and track objects that reside in deep space

John Salib 2 Jan 30, 2022
torchbearer: A model fitting library for PyTorch

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

631 Jan 04, 2023