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Found 8 papers, 3 papers with code
Structure-aware Fine-tuning for Code Pre-trained Models
Over the past few years, we have witnessed remarkable advancements in Code Pre-trained Models (CodePTMs).
MARVIS: Motion & Geometry Aware Real and Virtual Image Segmentation
By creating realistic synthetic images that mimic the complexities of the water surface, we provide fine-grained training data for our network (MARVIS) to discern between real and virtual images effectively.
An automated framework for brain vessel centerline extraction from CTA images
In this paper, we consider automatic lumen segmentation generation without additional annotation effort by physicians and more effective use of the generated lumen segmentation for improved centerline extraction performance.
KNVQA: A Benchmark for evaluation knowledge-based VQA
Within the multimodal field, large vision-language models (LVLMs) have made significant progress due to their strong perception and reasoning capabilities in the visual and language systems.
Multi-modal Fusion Technology based on Vehicle Information: A Survey
Multi-modal fusion is a basic task of autonomous driving system perception, which has attracted many scholars' interest in recent years.
UDepth: Fast Monocular Depth Estimation for Visually-guided Underwater Robots
Subsequently, we extend this into a domain projection loss that guides the end-to-end learning of UDepth on over 9K RGB-D training samples.
Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound
Breast cancer is one of the leading causes of cancer deaths in women.
Unsupervised single-particle deep clustering via statistical manifold learning
Motivation: Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination.
