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Found 4 papers, 1 papers with code
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations
Large-scale pretraining of visual representations has led to state-of-the-art performance on a range of benchmark computer vision tasks, yet the benefits of these techniques at extreme scale in complex production systems has been relatively unexplored.
Ranked #26 on
Image Classification
on ObjectNet
(using extra training data)
Toward Transformer-Based Object Detection
The Vision Transformer was the first major attempt to apply a pure transformer model directly to images as input, demonstrating that as compared to convolutional networks, transformer-based architectures can achieve competitive results on benchmark classification tasks.
Bootstrapping Complete The Look at Pinterest
In this paper, we will describe how we bootstrapped the Complete The Look (CTL) system at Pinterest.
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference
Homomorphic encryption enables arbitrary computation over data while it remains encrypted.
Cryptography and Security
