CSAILVision/GazeCapture resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1069 stars · 263 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

GazeCapture is a large-scale eye tracking dataset with ~2.5M frames from over 1450 subjects, released alongside the iTracker CNN model and Caffe code from the CVPR 2016 paper 'Eye Tracking for Everyone'. It enables gaze prediction on commodity mobile devices without extra sensors.

Use cases

• train a gaze estimation model on mobile phone images
• download a large eye tracking dataset for research
• reproduce the iTracker CNN from the CVPR 2016 paper
• benchmark gaze prediction error on phones and tablets
• study face and eye bounding box metadata for gaze datasets

When to choose

• you need large-scale real-world gaze data for training or benchmarking
• you want a research-licensed dataset with pretrained Caffe models
• you are reproducing or comparing against iTracker results

When to avoid

• you need a permissively licensed dataset for commercial use
• you need actively maintained PyTorch or TensorFlow code
• you need real-time eye tracking out of the box without training

Facets

dataset · maturity maintenance

computer-vision machine-learning deep-learning computer-vision machine-learning artificial-intelligence python cross-platform eye-tracking gaze-estimation dataset caffe itracker research

Member repositories

For agents

markdown · JSON · MCP: product_card(name="CSAILVision/GazeCapture")