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Found 4 papers, 4 papers with code
Pixel-Wise Recognition for Holistic Surgical Scene Understanding
This paper presents the Holistic and Multi-Granular Surgical Scene Understanding of Prostatectomies (GraSP) dataset, a curated benchmark that models surgical scene understanding as a hierarchy of complementary tasks with varying levels of granularity.
STRIDE: Street View-based Environmental Feature Detection and Pedestrian Collision Prediction
This paper introduces a novel benchmark to study the impact and relationship of built environment elements on pedestrian collision prediction, intending to enhance environmental awareness in autonomous driving systems to prevent pedestrian injuries actively.
MATIS: Masked-Attention Transformers for Surgical Instrument Segmentation
We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS), a two-stage, fully transformer-based method that leverages modern pixel-wise attention mechanisms for instrument segmentation.
Towards Holistic Surgical Scene Understanding
Second, we present Transformers for Action, Phase, Instrument, and steps Recognition (TAPIR) as a strong baseline for surgical scene understanding.
