DCSL - Generalizable Crowd Counting via Diverse Context Style Learning

Last update: Jun 13, 2022

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Deep Learning DCSL

Overview

DCSL

Generalizable Crowd Counting via Diverse Context Style Learning

Requirement:

python==3.8

pytorch==1.9.1

Test_datasets

链接: https://pan.baidu.com/s/1kChZgPQRCF4x0rAskaDpZw 提取码: ddqp

Parameters:

链接: https://pan.baidu.com/s/1wkXIho0P3HQXBCOMuGopXA 提取码: gap8

Test:

You can run test.py to test the model.

When loading the training parameters trained on which dataset to test the model,please modify models/backbones/model.py: num_class=num_class_SHA or num_class_SHB or num_class_QNRF.

For example,when use SHA.pth,please set num_class=num_class_SHA

Owner

GitHub Repository

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This is an official implementation for "PlaneRecNet".

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DCSL - Generalizable Crowd Counting via Diverse Context Style Learning

Related tags

Overview

DCSL

Requirement:

Test_datasets

Parameters:

Test:

Owner

This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild with Dense 3D Representations and A Benchmark. (CVPR 2022)"

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

⚓ Eurybia monitor model drift over time and securize model deployment with data validation

Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

SlotRefine: A Fast Non-Autoregressive Model forJoint Intent Detection and Slot Filling

DROPO: Sim-to-Real Transfer with Offline Domain Randomization

BOOKSUM: A Collection of Datasets for Long-form Narrative Summarization

This is an official implementation for "PlaneRecNet".

💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena

LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The original code is written in keras.

Official PyTorch Implementation of Mask-aware IoU and maYOLACT Detector [BMVC2021]

Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration

CSD: Consistency-based Semi-supervised learning for object Detection

First-Order Probabilistic Programming Language

Keras implementation of Deeplab v3+ with pretrained weights

Deep Learning Package based on TensorFlow

Predict multi paths to a moving person depending on his trajectory history.

Accompanying code for the paper "A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment".

Yolo Traffic Light Detection With Python