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Found 12 papers, 1 papers with code
LACOSTE: Exploiting stereo and temporal contexts for surgical instrument segmentation
In this work, we propose a novel LACOSTE model that exploits Location-Agnostic COntexts in Stereo and TEmporal images for improved surgical instrument segmentation.
PostoMETRO: Pose Token Enhanced Mesh Transformer for Robust 3D Human Mesh Recovery
With the recent advancements in single-image-based human mesh recovery, there is a growing interest in enhancing its performance in certain extreme scenarios, such as occlusion, while maintaining overall model accuracy.
Ranked #9 on
3D Human Pose Estimation
on 3DPW
WeakSurg: Weakly supervised surgical instrument segmentation using temporal equivariance and semantic continuity
We annotate instance-wise instrument labels with fixed time-steps which are double checked by a clinician with 3-years experience to evaluate segmentation results.
Sparse-view CT Reconstruction with 3D Gaussian Volumetric Representation
Sparse-view CT is a promising strategy for reducing the radiation dose of traditional CT scans, but reconstructing high-quality images from incomplete and noisy data is challenging.
Unsupervised augmentation optimization for few-shot medical image segmentation
The augmentation parameters matter to few-shot semantic segmentation since they directly affect the training outcome by feeding the networks with varying perturbated samples.
GDDS: Pulmonary Bronchioles Segmentation with Group Deep Dense Supervision
To address these problems, we contribute a new bronchial segmentation method based on Group Deep Dense Supervision (GDDS) that emphasizes fine-scale bronchioles segmentation in a simple-but-effective manner.
FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classification
Deep learning is becoming increasingly ubiquitous in medical research and applications while involving sensitive information and even critical diagnosis decisions.
MURPHY: Relations Matter in Surgical Workflow Analysis
Autonomous robotic surgery has advanced significantly based on analysis of visual and temporal cues in surgical workflow, but relational cues from domain knowledge remain under investigation.
Active CT Reconstruction with a Learned Sampling Policy
Experiments on the VerSe dataset demonstrate this ability of our sampling policy, which is difficult to achieve based on uniform sampling.
3D endoscopic depth estimation using 3D surface-aware constraints
We propose a loss function for depth estimation that integrates the surface-aware constraints, leading to a faster and better convergence with the valid information from spatial information.
The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods
For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging.
Learning to translate with products of novices: a suite of open-ended challenge problems for teaching MT
Machine translation (MT) draws from several different disciplines, making it a complex subject to teach.
