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Found 4 papers, 3 papers with code
MOFI: Learning Image Representations from Noisy Entity Annotated Images
Further experiments on zero-shot and linear probe image classification also show that MOFI outperforms a CLIP model trained on the original image-text data, demonstrating the effectiveness of the I2E dataset in learning strong image representations.
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
In an effort to help align the research community's contributions with real-world self-driving problems, we introduce a new large scale, high quality, diverse dataset.
Graph-RISE: Graph-Regularized Image Semantic Embedding
Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering.
Ranked #11 on
Image Classification
on iNaturalist
Detecting Cancer Metastases on Gigapixel Pathology Images
At 8 false positives per image, we detect 92. 4% of the tumors, relative to 82. 7% by the previous best automated approach.
Ranked #2 on
Medical Object Detection
on Barrett’s Esophagus
