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Found 5 papers, 2 papers with code
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding
Vision and vision-language applications of neural networks, such as image classification and captioning, rely on large-scale annotated datasets that require non-trivial data-collecting processes.
GlideNet: Global, Local and Intrinsic based Dense Embedding NETwork for Multi-category Attributes Prediction
Collectively, the Global-Local-Intrinsic blocks comprehend the scene's global context while attending to the characteristics of the local object of interest.
CAR -- Cityscapes Attributes Recognition A Multi-category Attributes Dataset for Autonomous Vehicles
We have also created an API for the dataset to ease the usage of CAR.
Natural Adversarial Objects
Moreover, by comparing a variety of object detection architectures, we find that better performance on MSCOCO validation set does not necessarily translate to better performance on NAO, suggesting that robustness cannot be simply achieved by training a more accurate model.
Ranked #1 on
Object Detection
on NAO
On The State of Data In Computer Vision: Human Annotations Remain Indispensable for Developing Deep Learning Models
High-quality labeled datasets play a crucial role in fueling the development of machine learning (ML), and in particular the development of deep learning (DL).
