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DETR: End-to-End Object Detection with Transformers
A new method that views object detection as a direct set prediction problem.
object-detection panoptic-segmentation transformers computer-vision
VirTex: Learning Visual Representations from Textual Annotations
We train CNN+Transformer from scratch from COCO, transfer the CNN to 6 downstream vision tasks, and exceed ImageNet features despite using 10x fewer ...
convolutional-neural-networks transformers coco visual-representations
T5 fine-tuning
A colab notebook to showcase how to fine-tune T5 model on various NLP tasks (especially non text-2-text tasks with text-2-text approach)
natural-language-processing transformers text-2-text t5
The Lottery Ticket Hypothesis: A Survey
Dive deeper into the lottery ticket hypothesis and review the literature after the original ICLR best paper award by Frankle & Carbin (2019).
lottery-ticket-hypothesis survey deep-learning article
NeuralCook — Image2Ingredients and Cooking Recommendation
Deep learning application to identify ingredients from cooking dishes images and recommend dishes to cook, given a set of ingredients.
cooking text-generation recommendation-systems joint-embeddings
How to Steal Modern NLP Systems with Gibberish?
It’s possible to steal BERT-based models without any real training data, even using gibberish word sequences.
bert adversarial-attacks computer-security adversarial-learning
Adversarial Latent Autoencoders
Introducing the Adversarial Latent Autoencoder (ALAE), a general architecture that can leverage recent improvements on GAN training procedures.
autoencoders generative-adversarial-networks latent-space disentanglement
STEFANN: Scene Text Editor using Font Adaptive Neural Network
A generalized method for realistic modification of textual content present in a scene image. ⭐️ Accepted in CVPR 2020.
scene-image scene-text-editor font-adaptive font-generation
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