ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

Last update: Dec 20, 2022

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Deep Learning AutoShape

Overview

AutoShape

ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

arXiv

Auto-labeling Car Shape for KITTI

We release our Auto-labeling car shape data for KITTI with COCO formate. Each car instance has been assigned a 3D model. Trainset and Valset with 3000 vertexes 3D models annotations can be download from Google Drive.

Data Formate

# we add 2D/3D keypoints in KITTI car instance annotations
annotations: [
    '2dkeypoints': list # (3000 + 9) * 3 (u, v, visiblity),
    '3dkeypoints': list # (3000 + 9) * 3 (x, y, z in model local coordinate)
    ...
    ], ...

Owner

Zongdai

GitHub Repository

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Face and other object detection using OpenCV and ML Yolo

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ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

Related tags

Overview

AutoShape

Auto-labeling Car Shape for KITTI

Data Formate

Owner

Zongdai

Leaderboard, taxonomy, and curated list of few-shot object detection papers.

python 93% acc. CNN Dogs Vs Cats ( Pytorch )

Simulating an AI playing 2048 using the Expectimax algorithm

Fast Neural Style for Image Style Transform by Pytorch

Deep Learning for Morphological Profiling

Human Dynamics from Monocular Video with Dynamic Camera Movements

Implementation of neural class expression synthesizers

This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks

Lua-parser-lark - An out-of-box Lua parser written in Lark

Face and other object detection using OpenCV and ML Yolo

B-cos Networks: Attention is All we Need for Interpretability

Using CNN to mimic the driver based on training data from Torcs

Temporal-Relational CrossTransformers

Kaggle competition: Springleaf Marketing Response

Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation

PyTorch implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.

[ACM MM 2021] TSA-Net: Tube Self-Attention Network for Action Quality Assessment

JAX bindings to the Flatiron Institute Non-uniform Fast Fourier Transform (FINUFFT) library

Adaptive Graph Convolution for Point Cloud Analysis