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Found 8 papers, 2 papers with code
TikTokActions: A TikTok-Derived Video Dataset for Human Action Recognition
We find that the performance of the model pre-trained using our Tik-Tok dataset is comparable to models trained on larger action recognition datasets (95. 3% on UCF101 and 53. 24% on HMDB51).
Benchmarking PathCLIP for Pathology Image Analysis
Additionally, we assess the robustness of PathCLIP in the task of image-image retrieval, revealing that PathCLIP performs less effectively than PLIP on Osteosarcoma but performs better on WSSS4LUAD under diverse corruptions.
WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Images
We benchmark our model on the largest subset of TCGA-PathoText.
Exploring Unsupervised Cell Recognition with Prior Self-activation Maps
The gradient information in the shallow layers of the network is aggregated to generate prior self-activation maps.
DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detection
Unlike mainstream PCD methods that rely on intermediate density map representations, the Point-to-Point network (P2PNet) has recently emerged as an end-to-end solution for PCD, demonstrating impressive cell detection accuracy and efficiency.
Unsupervised Dense Nuclei Detection and Segmentation with Prior Self-activation Map For Histology Images
To this end, we propose a self-supervised learning based approach with a Prior Self-activation Module (PSM) that generates self-activation maps from the input images to avoid labeling costs and further produce pseudo masks for the downstream task.
ChrSNet: Chromosome Straightening using Self-attention Guided Networks
Karyotyping is an important procedure to assess the possible existence of chromosomal abnormalities.
End-to-end cell recognition by point annotation
Reliable quantitative analysis of immunohistochemical staining images requires accurate and robust cell detection and classification.
