Surgical phase recognition
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Benchmarks
Most implemented
Pixel-Wise Recognition for Holistic Surgical Scene Understanding
HecVL: Hierarchical Video-Language Pretraining for Zero-shot Surgical Phase Recognition
Not End-to-End: Explore Multi-Stage Architecture for Online Surgical Phase Recognition
TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks
Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings
Papers
Large-Small Model Collaboration for Zero-Shot Surgical Phase Recognition
Task-specific lightweight models for surgical phase recognition excel at capturing temporal dynamics but generalize poorly under domain shift. Conversely, surgical foundation models (FMs) offer superior transferability v…
Surgical phase recognitionBeyond Instrument Motion: Recognizing Tissue Tension Toward Surgical Skill Assessment
Surgical performance assessment in minimally invasive surgery largely relies on manual expert review, making it time-consuming, subjective, and difficult to scale. While existing surgical video understanding methods addr…
Surgical phase recognitionAction RecognitionTemporally Consistent Label Interpolation for Robust Surgical Multi-Task Learning under Challenging Conditions
Effective multi-task learning for surgical scene understanding is fundamentally hindered by annotation granularity mismatch; temporal workflow tasks such as phase recognition, step recognition and anticipation benefit fr…
Surgical phase recognitionOptical Flow EstimationRepresentation LearningMulti-Task LearningGEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI
Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices - selecting the "best" global model based only on validation data f…
Surgical phase recognitionZero-shot GeneralizationFederated LearningPolyp SegmentationSurgicalMamba: Dual-Path SSD with State Regramming for Online Surgical Phase Recognition
Online surgical phase recognition must commit to a prediction at every frame of a procedure that runs for hours, from past frames alone and at a per-frame cost that does not grow with elapsed length. Structured state-spa…
Surgical phase recognitionStabilizing Temporal Inference Dynamics for Online Surgical Phase Recognition
Online Surgical Phase Recognition (SPR) models can reach high frame-wise accuracy, yet their predictions often lack temporal stability, fragmenting workflow understanding and reducing the reliability of downstream assist…
Surgical phase recognition