Papers with Code 아카이브
Surgical phase recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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The first 40 videos are used for training, the last 40 videos are used for testing.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement
Meta-SurDiff: Classification Diffusion Model Optimized by Meta Learning is Reliable for Online Surgical Phase Recognition
ReSW-VL: Representation Learning for Surgical Workflow Analysis Using Vision-Language Model
Surgeons vs. Computer Vision: A comparative analysis on surgical phase recognition capabilities
Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections
fine-CLIP: Enhancing Zero-Shot Fine-Grained Surgical Action Recognition with Vision-Language Models
Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings
MoSFormer: Augmenting Temporal Context with Memory of Surgery for Surgical Phase Recognition
EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training
ArthroPhase: A Novel Dataset and Method for Phase Recognition in Arthroscopic Video
Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition
Benchmarking and Enhancing Surgical Phase Recognition Models for Robotic-Assisted Esophagectomy
Neural Finite-State Machines for Surgical Phase Recognition
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin-based Scene Representation
SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition
SurgPLAN++: Universal Surgical Phase Localization Network for Online and Offline Inference
SPRMamba: Surgical Phase Recognition for Endoscopic Submucosal Dissection with Mamba
DACAT: Dual-stream Adaptive Clip-aware Time Modeling for Robust Online Surgical Phase Recognition
VidLPRO: A $\underline{Vid}$eo-$\underline{L}$anguage $\underline{P}$re-training Framework for $\underline{Ro}$botic and Laparoscopic Surgery
Surgformer: Surgical Transformer with Hierarchical Temporal Attention for Surgical Phase Recognition
MuST: Multi-Scale Transformers for Surgical Phase Recognition
SR-Mamba: Effective Surgical Phase Recognition with State Space Model
Robust Surgical Phase Recognition From Annotation Efficient Supervision
Towards Intelligent Speech Assistants in Operating Rooms: A Multimodal Model for Surgical Workflow Analysis
Thoracic Surgery Video Analysis for Surgical Phase Recognition
EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery Videos
HecVL: Hierarchical Video-Language Pretraining for Zero-shot Surgical Phase Recognition
SuPRA: Surgical Phase Recognition and Anticipation for Intra-Operative Planning
Friends Across Time: Multi-Scale Action Segmentation Transformer for Surgical Phase Recognition
Pixel-Wise Recognition for Holistic Surgical Scene Understanding
Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning
Surgical Temporal Action-aware Network with Sequence Regularization for Phase Recognition
SurgPLAN: Surgical Phase Localization Network for Phase Recognition
Weakly-Supervised Surgical Phase Recognition
Self-Supervised Learning for Endoscopic Video Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.