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Found 13 papers, 0 papers with code
Modeling Multimodal Social Interactions: New Challenges and Baselines with Densely Aligned Representations
Furthermore, we propose a novel multimodal baseline that leverages densely aligned language-visual representations by synchronizing visual features with their corresponding utterances.
Learning-based Bone Quality Classification Method for Spinal Metastasis
In this paper, we explore a learning-based automatic bone quality classification method for spinal metastasis based on CT images.
Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation
In this paper, we propose a Weakly supervised Iterative Spinal Segmentation (WISS) method leveraging only four corner landmark weak labels on a single sagittal slice to achieve automatic volumetric segmentation from CT images for VBs.
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning
Additionally, existing diffusion-based image manipulation models are sub-optimal in controlling the state transition of an action in egocentric image pixel space because of the domain gap.
Listen to Look into the Future: Audio-Visual Egocentric Gaze Anticipation
Motivated by this observation, we introduce the first model that leverages both the video and audio modalities for egocentric gaze anticipation.
Werewolf Among Us: A Multimodal Dataset for Modeling Persuasion Behaviors in Social Deduction Games
We also explore the generalization ability of language models for persuasion modeling and the role of persuasion strategies in predicting social deduction game outcomes.
In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation
To this end, we design the transformer encoder to embed the global context as one additional visual token and further propose a novel Global-Local Correlation (GLC) module to explicitly model the correlation of the global token and each local token.
A deep learning pipeline for localization, differentiation, and uncertainty estimation of liver lesions using multi-phasic and multi-sequence MRI
Results: the proposed CAD solution achieves a mean F1 score of 0. 62, outperforming the abdominal radiologist (0. 47), matching the junior hepatology radiologist (0. 61), and underperforming the senior hepatology radiologist (0. 68).
VeniBot: Towards Autonomous Venipuncture with Automatic Puncture Area and Angle Regression from NIR Images
For the automation, we focus on the positioning part and propose a Dual-In-Dual-Out network based on two-step learning and two-task learning, which can achieve fully automatic regression of the suitable puncture area and angle from near-infrared(NIR) images.
VeniBot: Towards Autonomous Venipuncture with Semi-supervised Vein Segmentation from Ultrasound Images
In the modern medical care, venipuncture is an indispensable procedure for both diagnosis and treatment.
Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph
It first trains a DAG model on the labeled data and then fine-tunes the pre-trained model on the unlabeled data with a teacher-student SSL mechanism.
Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Data
Lesion detection serves a critical role in early diagnosis and has been well explored in recent years due to methodological advancesand increased data availability.
Fully-Automated Liver Tumor Localization and Characterization from Multi-Phase MR Volumes Using Key-Slice ROI Parsing: A Physician-Inspired Approach
Using radiological scans to identify liver tumors is crucial for proper patient treatment.
