← All projects

Perception / 2026

PIXER

Learn which pixels to trust for more reliable, efficient visual navigation.

Quadruped robot outside Davis Hall with a visualization of reliable visual features
Quadruped robot outside Davis Hall with a visualization of reliable visual features

About the project

PIXER predicts a dense reliability map from a single image and filters low-utility features before matching. A lightweight self-supervised network makes this usable as a preprocessing step for feature-based visual navigation.

What it enables

Across eight feature detectors, the project reports improved trajectory accuracy while using fewer features.