ProtoTreeProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
Stars: ✭ 47 (+46.88%)
Mutual labels: fine-grained-classification, fine-grained-visual-categorization
AP-CNN Pytorch-masterWeakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification (TIP2021)
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Mutual labels: fine-grained, fine-grained-visual-categorization
PFNet-FGVCPFNet: A Novel Part Fusion Network for Fine-grained Visual Categorization
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Mutual labels: fine-grained-visual-categorization
ePillID-benchmarkePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification (CVPR 2020 VL3)
Stars: ✭ 54 (+68.75%)
Mutual labels: fine-grained-visual-categorization
agegenderLMTCNNJia-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
Stars: ✭ 39 (+21.88%)
Mutual labels: multi-task-learning
Pytorch-PCGradPytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
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Mutual labels: multi-task-learning
Mask-YOLOInspired 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.
Stars: ✭ 100 (+212.5%)
Mutual labels: multi-task-learning
EasyRecA framework for large scale recommendation algorithms.
Stars: ✭ 599 (+1771.88%)
Mutual labels: multi-task-learning
DeepSegmentorA Pytorch implementation of DeepCrack and RoadNet projects.
Stars: ✭ 152 (+375%)
Mutual labels: multi-task-learning
multi-task-learningMulti-task learning smile detection, age and gender classification on GENKI4k, IMDB-Wiki dataset.
Stars: ✭ 154 (+381.25%)
Mutual labels: multi-task-learning
temporal-depth-segmentationSource 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).
Stars: ✭ 20 (-37.5%)
Mutual labels: multi-task-learning
MTL-AQAWhat and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment [CVPR 2019]
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Mutual labels: fine-grained-classification
CLUEmotionAnalysis2020CLUE Emotion Analysis Dataset 细粒度情感分析数据集
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Mutual labels: fine-grained
cups-rlCustomisable 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"
Stars: ✭ 38 (+18.75%)
Mutual labels: multi-task-learning
torchMTLA lightweight module for Multi-Task Learning in pytorch.
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Mutual labels: multi-task-learning
FOCAL-ICLRCode for FOCAL Paper Published at ICLR 2021
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Mutual labels: multi-task-learning
PCC-NetPCC Net: Perspective Crowd Counting via Spatial Convolutional Network
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Mutual labels: multi-task-learning
mtlearnMulti-Task Learning package built with tensorflow 2 (Multi-Gate Mixture of Experts, Cross-Stitch, Ucertainty Weighting)
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Mutual labels: multi-task-learning
MNIST-multitask6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"
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Mutual labels: multi-task-learning
PartNetThe source code for the TMM paper: Part-Aware Fine-grained Object Categorization using Weakly Supervised Part Detection Network
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Mutual labels: fine-grained-visual-categorization