# Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse Surgical Instrument Usage for Context-aware Assistance

arXiv: https://arxiv.org/abs/2007.00548 · HTML: https://mlsanity.com/paper/2007.00548/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2020.

## Built on by (most cited first, 13 of 13)

- [Procedure-Aware Surgical Video-language Pretraining with Hierarchical Knowledge Augmentation](https://mlsanity.com/paper/2410.00263/) (2024)
- [On the Pitfalls of Batch Normalization for End-to-End Video Learning: A Study on Surgical Workflow Analysis](https://mlsanity.com/paper/2203.07976/) (2022)
- [SUPR-GAN: SUrgical PRediction GAN for Event Anticipation in Laparoscopic and Robotic Surgery](https://mlsanity.com/paper/2105.04642/) (2021)
- [OSSAR: Towards Open-Set Surgical Activity Recognition in Robot-assisted Surgery](https://mlsanity.com/paper/2402.06985/) (2024)
- [Towards Graph Representation Learning Based Surgical Workflow Anticipation](https://mlsanity.com/paper/2208.03824/) (2022)
- [Multitask Learning in Minimally Invasive Surgical Vision: A Review](https://mlsanity.com/paper/2401.08256/) (2024)
- [SWAG: Long-term Surgical Workflow Prediction with Generative-based Anticipation](https://mlsanity.com/paper/2412.18849/) (2024)
- [SuPRA: Surgical Phase Recognition and Anticipation for Intra-Operative Planning](https://mlsanity.com/paper/2403.06200/) (2024)
- [Adaptive Graph Learning from Spatial Information for Surgical Workflow Anticipation](https://mlsanity.com/paper/2412.06454/) (2024)
- [Surgical Video Understanding with Label Interpolation](https://mlsanity.com/paper/2509.18802/) (2025)
- [CoStoDet-DDPM: Collaborative Training of Stochastic and Deterministic Models Improves Surgical Workflow Anticipation and Recognition](https://mlsanity.com/paper/2503.10216/) (2025)
- [State-Change Learning for Prediction of Future Events in Endoscopic Videos](https://mlsanity.com/paper/2510.12904/) (2025)
- [Temporally Consistent Label Interpolation for Robust Surgical Multi-Task Learning under Challenging Conditions](https://mlsanity.com/paper/2606.26634/) (2026)

## Abstract (arXiv)

Intra-operative anticipation of instrument usage is a necessary component for context-aware assistance in surgery, e.g. for instrument preparation or semi-automation of robotic tasks. However, the sparsity of instrument occurrences in long videos poses a challenge. Current approaches are limited as they assume knowledge on the timing of future actions or require dense temporal segmentations during training and inference. We propose a novel learning task for anticipation of instrument usage in laparoscopic videos that overcomes these limitations. During training, only sparse instrument annotations are required and inference is done solely on image data. We train a probabilistic model to address the uncertainty associated with future events. Our approach outperforms several baselines and is competitive to a variant using richer annotations. We demonstrate the model's ability to quantify task-relevant uncertainties. To the best of our knowledge, we are the first to propose a method for anticipating instruments in surgery.