3 days participate in #CVPR2020 conference. excited about a lot of interesting subjects covered in computer vision: Adversarial Learning, Effective training and inference, representation learning...
Will do a write-up later.
#CVPR20 #computervision
Will do a write-up later.
#CVPR20 #computervision
Some preferred papers so far 👇
1. Dynamic Graph Message Passing Networks arxiv.org/pdf/1908.06955…
It addresses the modelling long-range dependencies problem by using feature map as a feature vector nodes and dynamically sample the neighborhood of a node from the feature graph.
1. Dynamic Graph Message Passing Networks arxiv.org/pdf/1908.06955…
It addresses the modelling long-range dependencies problem by using feature map as a feature vector nodes and dynamically sample the neighborhood of a node from the feature graph.
2. Semantic Pyramid for Image Generation arxiv.org/pdf/2003.06221…
A generative image model that can leverage the feature space from different semantic levels learned by a pretrained classification network. many generative applications to play with
A generative image model that can leverage the feature space from different semantic levels learned by a pretrained classification network. many generative applications to play with
3. Momentum Contrast for Unsupervised Visual Representation Learning arxiv.org/pdf/1911.05722…
Inspired by idea of Bert in #nlp, the authors propose to contruct a large and consistent dictionnaries for unsupervised learning with constrative loss.
Inspired by idea of Bert in #nlp, the authors propose to contruct a large and consistent dictionnaries for unsupervised learning with constrative loss.
Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics arxiv.org/pdf/2004.02331…
I found it quite similar representation learning idea as Electra in #nlp. It proposes Limited Context Inpainting by masking regions of image and disciminate different transformations
I found it quite similar representation learning idea as Electra in #nlp. It proposes Limited Context Inpainting by masking regions of image and disciminate different transformations
5. Revisting knowledge distillation via label smoothing regularization arxiv.org/pdf/1909.11723…
The authors challenge the common belief in knowledge distillation by showing that the student can also enhance the teacher significantly and poorly trained-teacher can help the student
The authors challenge the common belief in knowledge distillation by showing that the student can also enhance the teacher significantly and poorly trained-teacher can help the student
6. PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization arxiv.org/pdf/2004.00452…
#FAIR researchers did an amazing job on human 3D model from a single image! impressive results!
#FAIR researchers did an amazing job on human 3D model from a single image! impressive results!
7. EfficientDet: Scalable and Efficient Object Detection arxiv.org/pdf/1911.09070…
A paper on Model efficiency of object detection by introducing weighted bi-directional feature pyramid network (BiFPN) for efficient multi-scale feature fusion and a novel compound scaling method
A paper on Model efficiency of object detection by introducing weighted bi-directional feature pyramid network (BiFPN) for efficient multi-scale feature fusion and a novel compound scaling method
8. Adversarial Latent Autoencoders arxiv.org/pdf/2004.04467…
The authors propose an autoencoder which can generate images with quality comparable to state-of-the-art GANs while also learning a less entangled representation.
Some impressive results with reconstruction of images:
The authors propose an autoencoder which can generate images with quality comparable to state-of-the-art GANs while also learning a less entangled representation.
Some impressive results with reconstruction of images:
@threadreaderapp unroll
