MEAL-V2 VS MEAL

Compare MEAL-V2 vs MEAL and see what are their differences.

MEAL-V2

MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop. (by szq0214)

MEAL

Official Implementation of MEAL: Multi-Model Ensemble via Adversarial Learning on AAAI 2019 (by AaronHeee)
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MEAL-V2 MEAL
1 2
684 173
- -
1.8 10.0
over 2 years ago about 4 years ago
Python Python
- -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

MEAL-V2

Posts with mentions or reviews of MEAL-V2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-26.

MEAL

Posts with mentions or reviews of MEAL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-26.

What are some alternatives?

When comparing MEAL-V2 and MEAL you can also consider the following projects:

segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

gen-efficientnet-pytorch - Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS

OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration

ModelZoo.pytorch - Hands on Imagenet training. Unofficial ModelZoo project on Pytorch. MobileNetV3 Top1 75.64🌟 GhostNet1.3x 75.78🌟

S2-BNN - S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)