3D Classification
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Benchmarks
Most implemented
Learning SO(3) Equivariant Representations with Spherical CNNs
Projector Is All You Train
Virtual imaging trials improved the transparency and reliability of AI systems in COVID-19 imaging
Robustifying Point Cloud Networks by Refocusing
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
Papers
Projector Is All You Train
The typical training process of a multimodal large language model (MLLM) involves adapting both the language model backbone and the projector between the backbone and a modality-specific encoder. We ask whether fine-tuni…
Spatial Reasoning3D Classification3D Classification of Paramagnetic Rim Lesions in Multiple Sclerosis via Asymmetric QSM-FLAIR Modeling
Paramagnetic rim lesions (Rim$^+$) identified on susceptibility-sensitive MRI have recently emerged as a specific biomarker of chronic active inflammation in Multiple Sclerosis (MS) and are associated with long-term disa…
Multimodal Deep Learning3D ClassificationPointLLM-R: Enhancing 3D Point Cloud Reasoning via Chain-of-Thought
Understanding 3D point clouds through language remains a fundamental challenge in computer graphics and visual computing, due to the irregular structure of point cloud data and the lack of explicit reasoning in existing …
3D ClassificationPoint CloudsAGA3DNet: Anatomy-Guided Gaussian Priors with Multi-view xLSTM for 3D Brain MRI Subtype Classification
Accurate 3D brain MRI subtype classification benefits from both localized anatomical cues and long-range contextual reasoning. We present AGA3DNet, a report-grounded framework that incorporates brief anatomical phrases e…
3D ClassificationDeep Reprogramming Distillation for Medical Foundation Models
Medical foundation models pre-trained on large-scale datasets have shown powerful versatile performance. However, when adapting medical foundation models for specific medical scenarios, it remains the inevitable challeng…
parameter-efficient fine-tuningKnowledge Distillation3D ClassificationFDIF: Formula-Driven supervised Learning with Implicit Functions for 3D Medical Image Segmentation
Deep learning-based 3D medical image segmentation methods relies on large-scale labeled datasets, yet acquiring such data is difficult due to privacy constraints and the high cost of expert annotation. Formula-Driven Sup…
Medical Image SegmentationRepresentation Learning3D Classification