30 Open source projects that are alternatives of or similar to NeuralMerger

Jia-Hong Lee, Yi-Ming Chan, Ting-Yen Chen, and Chu-Song Chen, "Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications," IEEE International Conference on Multimedia Information Processing and Retrieval, MIPR 2018

(CVPR 2021, Oral) Dynamic Slimmable Network

Multi-Task Deep Neural Networks for Natural Language Understanding

Multi-task deep learning framework for multi-omics data analysis

A deep learning framework for building multimodal multi-task learning systems.

HyperFace

Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen, "Compacting, Picking and Growing for Unforgetting Continual Learning," Thirty-third Conference on Neural Information Processing Systems, NeurIPS 2019

Deep Recommenders

Code release for Your “Flamingo” is My “Bird”: Fine-Grained, or Not (CVPR 2021 Oral)

Multi-Task Learning package built with tensorflow 2 (Multi-Gate Mixture of Experts, Cross-Stitch, Ucertainty Weighting)

PCC Net: Perspective Crowd Counting via Spatial Convolutional Network

6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"

A lightweight module for Multi-Task Learning in pytorch.

A framework for large scale recommendation algorithms.

A Pytorch implementation of DeepCrack and RoadNet projects.

Inspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.

Multi-task learning smile detection, age and gender classification on GENKI4k, IMDB-Wiki dataset.

Source code (train/test) accompanying the paper entitled "Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach" in CVPR 2019 (https://arxiv.org/abs/1903.10764).

A prototype version of our submitted paper: Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives.

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"

Code for FOCAL Paper Published at ICLR 2021

Asymmetric Multi-Task Attention Network for Prostate Bed Segmentation in CT Images

CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.

[CVPR 2021] Exploring Sparsity in Image Super-Resolution for Efficient Inference

Pytorch version of the HyperDenseNet deep neural network for multi-modal image segmentation

[CVPR2020] Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation

An open source implementation of CLIP.

A python tool to perform deep learning experiments on multimodal remote sensing data.

[ICCV 2021] TRAR: Routing the Attention Spans in Transformers for Visual Question Answering -- Official Implementation