Search Results for author:
Found 6 papers, 3 papers with code
AttEntropy: Segmenting Unknown Objects in Complex Scenes using the Spatial Attention Entropy of Semantic Segmentation Transformers
In other words, vision transformers trained to segment a fixed set of object classes generalize to objects well beyond this set.
Perspective Aware Road Obstacle Detection
While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases.
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation
State-of-the-art semantic or instance segmentation deep neural networks (DNNs) are usually trained on a closed set of semantic classes.
Detecting Road Obstacles by Erasing Them
Vehicles can encounter a myriad of obstacles on the road, and it is impossible to record them all beforehand to train a detector.
Detecting the Unexpected via Image Resynthesis
In this paper, we tackle the more realistic scenario where unexpected objects of unknown classes can appear at test time.
Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation
In this paper, we explicitly model the scale changes and reason in terms of people per square-meter.
