Pyramid Pooling Transformer for Scene Understanding

Related tags

Deep LearningP2T
Overview

Pyramid Pooling Transformer for Scene Understanding

Requirements:

  • torch 1.6+
  • torchvision 0.7.0
  • timm==0.3.2
  • Validated on torch 1.6.0, torchvision 0.7.0

Models Pretrained on ImageNet1K

Variants Input Size [email protected] [email protected] #Params (M) Pretrained Models
P2T-Tiny 224 x 224 78.1 94.1 11.1 Google Drive
P2T-Small 224 x 224 82.1 95.9 23.0 Google Drive
P2T-Base 224 x 224 83.0 96.2 36.2 Google Drive

Pretrained Models for Downstream tasks

To be updated.

Something Else

Note: we have prepared a stronger version of P2T. Since P2T is still in peer review, we will release the stronger P2T after the acceptance.

You might also like...
Neural Scene Graphs for Dynamic Scene (CVPR 2021)
Neural Scene Graphs for Dynamic Scene (CVPR 2021)

Implementation of Neural Scene Graphs, that optimizes multiple radiance fields to represent different objects and a static scene background. Learned representations can be rendered with novel object compositions and views.

null 151 Dec 26, 2022
A weakly-supervised scene graph generation codebase. The implementation of our CVPR2021 paper ``Linguistic Structures as Weak Supervision for Visual Scene Graph Generation''
A weakly-supervised scene graph generation codebase. The implementation of our CVPR2021 paper ``Linguistic Structures as Weak Supervision for Visual Scene Graph Generation''

README.md shall be finished soon. WSSGG 0 Overview 1 Installation 1.1 Faster-RCNN 1.2 Language Parser 1.3 GloVe Embeddings 2 Settings 2.1 VG-GT-Graph

Keren Ye 35 Nov 20, 2022
Automatic number plate recognition using tech: Yolo, OCR, Scene text detection, scene text recognation, flask, torch
Automatic number plate recognition using tech: Yolo, OCR, Scene text detection, scene text recognation, flask, torch

Automatic Number Plate Recognition Automatic Number Plate Recognition (ANPR) is the process of reading the characters on the plate with various optica

Meftun AKARSU 52 Dec 22, 2022
Pytorch implementation of Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
Pytorch implementation of Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors

Make-A-Scene - PyTorch Pytorch implementation (inofficial) of Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors (https://arxiv.org/

Casual GAN Papers 259 Dec 28, 2022
Code for
Code for "Learning the Best Pooling Strategy for Visual Semantic Embedding", CVPR 2021

Learning the Best Pooling Strategy for Visual Semantic Embedding Official PyTorch implementation of the paper Learning the Best Pooling Strategy for V

Jiacheng Chen 106 Jan 6, 2023
Source code for paper "Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling", AAAI 2021

ATLOP Code for AAAI 2021 paper Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling. If you make use of this co

Wenxuan Zhou 146 Nov 29, 2022
This repository is an open-source implementation of the ICRA 2021 paper: Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling.
This repository is an open-source implementation of the ICRA 2021 paper: Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling.

Locus This repository is an open-source implementation of the ICRA 2021 paper: Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order

Robotics and Autonomous Systems Group 96 Dec 15, 2022
Compact Bilinear Pooling for PyTorch

Compact Bilinear Pooling for PyTorch. This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch. This

Grégoire Payen de La Garanderie 234 Dec 7, 2022
A Pytorch Implementation for Compact Bilinear Pooling.

CompactBilinearPooling-Pytorch A Pytorch Implementation for Compact Bilinear Pooling. Adapted from tensorflow_compact_bilinear_pooling Prerequisites I

null 169 Dec 23, 2022
Comments
  • How to load ImageNet1K pretrained weight to semantic segmentation model?

    How to load ImageNet1K pretrained weight to semantic segmentation model?

    Hello, thanks for open source!

    I use mmseg, and load weight from image classification result, it warns: WARNING - The model and loaded state dict do not match exactly missing keys in source state_dict: backbone.head.weight, backbone.head.bias unexpected key in source state_dict: cls_token, ln1.bias, ln1.weight, layers.0.ln1.bias, layers.0.ln1.weight, layers.0.ln2.bias, layers.0.ln2.weight, layers.0.ffn.layers.0.0.bias, layers.0.ffn.layers.0.0.weight, layers.0.ffn.layers.1.bias, layers.0.ffn.layers.1.weight, layers.0.attn.attn.out_proj.bias, layers.0.attn.attn.out_proj.weight, layers.0.attn.attn.in_proj_bias, layers.0.attn.attn.in_proj_weight, layers.1.ln1.bias, layers.1.ln1.weight, layers.1.ln2.bias, layers.1.ln2.weight, layers.1.ffn.layers.0.0.bias, layers.1.ffn.layers.0.0.weight, layers.1.ffn.layers.1.bias, layers.1.ffn.layers.1.weight, layers.1.attn.attn.out_proj.bias, layers.1.attn.attn.out_proj.weight ...... And the experimental results are terrible as the experiments initialize weight with random.

    So I load weight from ADE20K result, it work and warns: WARNING - The model and loaded state dict do not match exactly missing keys in source state_dict: backbone.head.weight, backbone.head.bias And the result is similar to the result you offer.

    Which weight should I load? ImageNet1K or ADE20K? Or should I modify the keys of weight in ImageNet1K to adapt the key in segmentation?

    opened by asd123pwj 8
  • Questions about your ablation studies

    Questions about your ablation studies

    Hello,

    I have some questions about your ablation studies of pyramid pooling. Could you detail about your baseline version in Table 9? First, you say that you replace P-MHSA with an MHSA with a single pooling operation, what is the detail about single pooling operation? Ex: Pooling Ratios? Second, do you compared your method with original MHSA?

    opened by pp00704831 3
  • P2T replaces PVT trunk bug

    P2T replaces PVT trunk bug

    When I replaced the PVT trunk with P2T in my code, I encountered an error ：
    RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [16, 512, 3, 3]], which is output 0 of AdaptiveAvgPool2DBackward, is at version 1; expected version 0 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).

    opened by liu-tianxiang 2
  • P2T on ImageNet-22K?

    P2T on ImageNet-22K?

    Hi @yuhuan-wu , thank you for share the code of this excellent work! Have you trained P2T on ImageNet-22K dataset or any further plan to do it? If so, could you please share the pretrained model on ImageNet-22k?

    Thank you.

    opened by fyaft2012 1
Owner
Yu-Huan Wu
Ph.D. student at Nankai University
Yu-Huan Wu
GitHub Repository
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

Attention Walk ⠀⠀ A PyTorch Implementation of Watch Your Step: Learning Node Embeddings via Graph Attention (NIPS 2018). Abstract Graph embedding meth

Benedek Rozemberczki 303 Dec 09, 2022
Code release for The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification (TIP 2020)

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel

PRIS-CV: Computer Vision Group 230 Dec 31, 2022
This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization

Spherical Gaussian Optimization This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization. This code has b

41 Dec 14, 2022
Code for the paper "Generative design of breakwaters usign deep convolutional neural network as a surrogate model"

Generative design of breakwaters usign deep convolutional neural network as a surrogate model This repository contains the code for the paper "Generat

2 Apr 10, 2022
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang 1.2k Dec 29, 2022
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection

Why, hello there! This is the supporting notebook for the research paper — Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomal

2 Dec 14, 2021
CLIP: Connecting Text and Image (Learning Transferable Visual Models From Natural Language Supervision)

CLIP (Contrastive Language–Image Pre-training) Experiments (Evaluation) Model Dataset Acc (%) ViT-B/32 (Paper) CIFAR100 65.1 ViT-B/32 (Our) CIFAR100 6

Myeongjun Kim 52 Jan 07, 2023
RL and distillation in CARLA using a factorized world model

World on Rails Learning to drive from a world on rails Dian Chen, Vladlen Koltun, Philipp Krähenbühl, arXiv techical report (arXiv 2105.00636) This re

Dian Chen 131 Dec 16, 2022
Pytorch Implementation of Auto-Compressing Subset Pruning for Semantic Image Segmentation

Pytorch Implementation of Auto-Compressing Subset Pruning for Semantic Image Segmentation Introduction ACoSP is an online pruning algorithm that compr

Merantix 8 Dec 07, 2022
MASS (Mueen's Algorithm for Similarity Search) - a python 2 and 3 compatible library used for searching time series sub-sequences under z-normalized Euclidean distance for similarity.

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

Matrix Profile Foundation 79 Dec 31, 2022
TorchMetrics is a collection of 25+ PyTorch metrics implementations and an easy-to-use API to create custom metrics.

Machine learning metrics for distributed, scalable PyTorch applications.

Pytorch Lightning 1.2k Jan 06, 2023
QI-Q RoboMaster2022 CV Algorithm

QI-Q RoboMaster2022 CV Algorithm

2 Jan 10, 2022
[ECCV 2020] Gradient-Induced Co-Saliency Detection

Gradient-Induced Co-Saliency Detection Zhao Zhang*, Wenda Jin*, Jun Xu, Ming-Ming Cheng ⭐ Project Home » The official repo of the ECCV 2020 paper Grad

Zhao Zhang 35 Nov 25, 2022
Rethinking Portrait Matting with Privacy Preserving

Rethinking Portrait Matting with Privacy Preserving This is the official repository of the paper Rethinking Portrait Matting with Privacy Preserving.

184 Jan 03, 2023
Learning Energy-Based Models by Diffusion Recovery Likelihood

Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma Paper: https://arxiv.o

Ruiqi Gao 41 Nov 22, 2022
Learn about quantum computing and algorithm on quantum computing

quantum_computing this repo contains everything i learn about quantum computing and algorithm on quantum computing what is aquantum computing quantum

arfy slowy 8 Dec 25, 2022
An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

Kakao Brain 72 Dec 28, 2022
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c

Nguyen Mau Dung 438 Dec 29, 2022
Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning"

Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning" This is the code for the paper Solving Graph-based Public Goo

Victor-Alexandru Darvariu 3 Dec 05, 2022
Project for tracking occupancy in Tel-Aviv parking lots.

Ahuzat Dibuk - Tracking occupancy in Tel-Aviv parking lots main.py This module was set-up to be executed on Google Cloud Platform. I run it every 15 m

Geva Kipper 35 Nov 22, 2022