ilke Profile picture
14 Nov, 8 tweets, 4 min read
Are you trying to visualize your deep network just 2 days before the #CVPR2021 deadline? Here are some pretty alternatives to boring tensorboard graphs. (1/n)
Tensorspace: tensorspace.org
Fun, interactive, 3D, and you can zoom into a specific layer for samples. (2/n)
PlotNeuralNet: github.com/HarisIqbal88/P…
Pretty visualizations with direct export to tex!
overleaf.com/project/5ee510… (3/n)
Moniel: github.com/mlajtos/moniel
Although discontinued, plug-n-play graph construction with simple primitives. (4/n)
NN SVG: alexlenail.me/NN-SVG/LeNet.h…
Web UI for generating FCN, AlexNet, and LeNet-like architectures. (5/n)
Netron: netron.app
Neural network file viewer, (experimentally) supports most of the model formats. (6/n)
ENNUI: math.mit.edu/ennui/
This might be my favorite. You can ensemble AND train AND analyze the network online! (7/n)
There is also tensorboard (pytorch.org/docs/stable/te…), torchviz (github.com/szagoruyko/pyt…), and hiddenlayer (github.com/waleedka/hidde…), all of which may be stronger on the analysis side than the visualization side. Let me know if I missed any! (8/8)

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More from @ilkedemir

19 Jun
Last day of the main conference at #CVPR2020, and here are my non-scientifically chosen top five papers @CVPR for the last day. Visit them in the next 10(?) hours! (1/6)
1. High-Dimensional Convolutional Networks for Geometric Pattern Recognition

Authors: Christopher Choy, Junha Lee, René Ranftl, Jaesik Park, Vladlen Koltun

Correspondences in 2D/3D forms geometric structures in higher dim, let's segment those with ND convnets!

#CVPR2020 Image
2. PointGMM: A Neural GMM Network for Point Clouds

Authors: Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or

Constructing a hierarchical GMM by attentional split, and using the encoding for shape interpolation and generation.

#CVPR2020 ImageImage
Read 8 tweets
18 Jun
For the night session attendees of #CVPR2020, here is my completely non-scientifically chosen top five papers @cvpr for the second day. Visit them in the next 8 hours! (1/6)
1. DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes

Authors: Jonas Schult, Francis Engelmann, Theodora Kontogianni, Bastian Leibe

Conv->(euclidean+geodesic) convs
Pooling->mesh simplification
6% mIoU increase and a nice paper!

#CVPR2020
2. Unsupervised Learning of Intrinsic Structural Representation Points

Authors: Nenglun Chen, Lingjie Liu, Zhiming Cui, Runnan Chen, Duygu Ceylan, Changhe Tu, Wenping Wang

Like categorical SIFT points in point clouds, for matching, recon, interpolation and more!

#CVPR2020
Read 7 tweets
17 Jun
For the night session attendees of #CVPR2020, here is my completely non-scientifically chosen top five papers @cvpr first day. Visit them in the next 8 hours! (1/6)
1. Perspective Plane Program Induction From a Single Image
Authors: Yikai Li, Jiayuan Mao, Xiuming Zhang, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu @MIT_CSAIL

Domain agnostic image-based proceduralization with single terminal and grid-based rules.

#CVPR2020 Day 1
2. Learning Formation of Physically-Based Face Attributes

Authors: Ruilong Li, Karl Bladin, Yajie Zhao, Chinmay Chinara, Owen Ingraham, Pengda Xiang, Xinglei Ren, et al. @HaoLi81

Photorealistic humans are here! Fitting code for any 3D mesh is coming soon too.

#CVPR2020 Day 1
Read 7 tweets

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