AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation

Last update: Dec 13, 2022

Related tags

Overview

AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation

A pytorch-version implementation codes of paper: "AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation", which is accepted in BMVC 2021.

Prerequisites

Python 3.8
Pytorch 1.9
fvcore
numpy, pandas, matplotlib, tensorboardX etc.

Download Features

3D Resnet-50 features extracted from rescaled videos of ActivityNet-1.3 can be downloaded [here](will be updated soon).

Training and Testing of AEI

Default configurations of AEI are stored in config/defaults.py. The modified configurations are stored in config/*.yaml for training and testing of AEI on different datasets (ActivityNet-1.3 and THUMOS-14). We can also modify configurations through commandline arguments.

To train AEI on TAPG task of ActivityNet-1.3 with 1 GPU:

python main.py --cfg-file config/anet_proposals.yaml MODE 'training' GPU_IDS [0]

To evaluate AEI on validation set of ActivityNet-1.3 with 1 GPU:

python main.py --cfg-file config/anet_proposals.yaml MODE 'validation' GPU_IDS [0]

Reference

This implementation is partly based on this pytorch-implementation of BMN.

paper:[AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation](will update soon)

AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation

Related tags

Overview

AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation

Prerequisites

Download Features

Training and Testing of AEI

Reference

Owner

Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.

D2LV: A Data-Driven and Local-Verification Approach for Image Copy Detection

End-to-end Temporal Action Detection with Transformer. [Under review]

This is an official implementation for "PlaneRecNet".

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Simulation of Self Driving Car

Implementation of the "Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos" paper.

Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.

UniFormer - official implementation of UniFormer

CKD - Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding

This repo contains the official code and pre-trained models for the Dynamic Vision Transformer (DVT).

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

Code for "Adversarial Attack Generation Empowered by Min-Max Optimization", NeurIPS 2021

Yolox-bytetrack-sample - Python sample of MOT (Multiple Object Tracking) using YOLOX and ByteTrack

Customizable RecSys Simulator for OpenAI Gym

Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness

Gin provides a lightweight configuration framework for Python

Neural Scene Flow Prior (NeurIPS 2021 spotlight)

SafePicking: Learning Safe Object Extraction via Object-Level Mapping, ICRA 2022