April 13 2017
Breakthrough on the French Street Names dataset. This paper boasts a huge improvement over previous state-of-the-art models including Inception V3 and Inception Resnet V2. And since that wasn’t hard enough, they also tested it against Google Street View, cause it’s all like nbd.
What’s better than BEGAN? MAGAN! Or at least that’s what the authors of this paper are saying. They are probably right because a) they have a simpler setup and b) they use public datasets so their work is reproducible. Plus they are promising to release the code on Github in the near future.
New 3d point cloud dataset and benchmark with semantic labels. Should be a lot of use to people doing AR. They did a nice job with the benchmark too, and have an automated submission process with a public leaderboard.
April 12 2017
There’s a lot of research around VQA right now. This new paper gets a new state-of-the-art on VQA 1, an improvement of 0.4%. It’s by a small margin, but it’s also using a simpler architecture.
Autoencoding for networks. Struc2Vec gives you a new way to view and understand your networks.
New paper out of Stanford, Pennsylvania State and Google Brain delves into what happens when a ML model is attacked, and how to incorporate robustness. It’s an interesting read in an interesting space.
April 11 2017
Not just for pong, this paper simulates environments from 2d Atari games to 3d racing sims. It has DQN Scores on a bunch of games (and goes into high detail on how they got those scores), but they don’t explicitly compare those score with current state-of-the-art.
Building a recommendation engine? This paper gets a new state-of-the-art on ratings predictions. Show your users what they want to see.
April 07 2017
I am looking forward to the day when I can write a model that writes models for me. Maybe someone will turn it into an API and I won’t have to write anything. This paper gets us another step closer. Working with Python and other high-level languages, they have a new state of the art in code generation.
Telling the difference between various types of red sedans or crows is hard for humans, let alone neural nets. This paper does it better and cheaper.
Looking for ways to generate a FAQ from your docs? This paper points to a potential direction.
April 06 2017
The next time we do a Kaggle comptition we’ll try this technique. When working on an image segmentation problem, it’s those last couple pixels around the edges that make all the difference in your mIoU.
When training an image classifier, one of the things we normally do is add noise to the dataset. This paper tackles the inverse problem (denoising) and adds semantic information to their images. Using ImageNet as their test set, the results are really compelling and show tons of promise / future research.
Change detection datasets can be hard to come by. Especially so with low altitude geolocated drone datasets. While there’s a lot of opportunity for mis-use of research and we’re uncomfortable with all the scenarios presented, there’s also a lot of humanitarian use cases as well. Drone delivery of medication to natural disaster areas is just one that comes to mind.
April 05 2017
Want to build a faster / better image search? Combine your hashing and aggregating systems. Or at least that’s the advice from a new paper out of Baidu research yesterday. The storage space needed gets a bit larger, but you reap the benefits of a much faster lookup.
State Of The Art Results
- Apr 13 General Approach to Real World Text Extraction
- Apr 13 MAGAN, Better than BEGAN
- Apr 12 New SOTA for VQA 1.0
- Apr 11 Predicting Recomendations with TransNets
- Apr 7 Use Machine Learning to Write Your Code For You
- Apr 5 Build A Faster Image Search
- Apr 5 2D to 3D Depth in Noisy Environments
- Apr 4 New State of The Art on Keyphrase Boundary Classification
- Apr 4 New State of the Art In Semantic Role Labeling
- Apr 3 State-Of-The-Art Foreground Object Detection
- Apr 15 Neural Paraphrase Identification of Questions with Noisy Pretraining
- Apr 13 3d Point Cloud Dataset and Benchmark
- Apr 10 Loss Max-Pooling for Semantic Image Segmentation
- Apr 9 BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis
- Apr 6 A Low Altitude Geo-Referenced Drone Dataset
- Apr 3 Auto-Encode Your Way to Realistic Images
- Mar 21 Boost Your Cross-Media Retrieval Process with Twitter100k
- Mar 21 Counterfactual Fairness: Combat the Inherent Social Biases of Your Dataset
- Apr 20 Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption
- Apr 20 Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency
- Apr 20 Towards Large-Pose Face Frontalization in the Wild
- Apr 20 Temporal Action Detection with Structured Segment Networks
- Apr 20 Reinforcement Learning with External Knowledge and Two-Stage Q-functions for Predicting Popular Reddit Threads
- Apr 20 On Singleton Arc Consistency for Natural CSPs Defined by Forbidden Patterns
- Apr 20 Dynamic Graph Convolutional Networks
- Apr 20 Improved Neural Relation Detection for Knowledge Base Question Answering
- Apr 20 Intrusion Prevention and Detection in Grid Computing - The ALICE Case
- Apr 20 Softmax GAN
- Apr 20 Training object class detectors with click supervision
- Apr 20 Exploring epoch-dependent stochastic residual networks
- Apr 20 Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks
- Apr 20 Learning to Acquire Information
- Apr 20 BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMs
- Apr 20 Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation
- Apr 20 Neural End-to-End Learning for Computational Argumentation Mining
- Apr 20 The Dependent Doors Problem: An Investigation into Sequential Decisions without Feedback
- Apr 20 Knowledge Fusion via Embeddings from Text, Knowledge Graphs, and Images
- Apr 20 End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network