Papers with Code 아카이브

Object Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 3
평가표: 9
보존된 평가 기록: 31

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/fpv-iplab/MECCANO

공식 코드

The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain

https://github.com/gabrieleciravegna/knowledge-driven-active-learning

공식 코드

Knowledge-driven Active Learning

https://github.com/garygsw/smooth-taylor

공식 코드

Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution

https://github.com/georgekillick90/fovconvnext

공식 코드

Foveation in the Era of Deep Learning

https://github.com/gidariss/FewShotWithoutForgetting

공식 코드

Dynamic Few-Shot Visual Learning without Forgetting

https://github.com/giparisi/GDM

공식 코드

Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization

https://github.com/git-disl/TOG

공식 코드

TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems

https://github.com/github-songsong/fine-grained-pointcloud-object-dataset

공식 코드

Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models

https://github.com/golnazghiasi/cofw68-benchmark

공식 코드

Occlusion Coherence: Detecting and Localizing Occluded Faces

https://github.com/golnazghiasi/hpm-detection-code

공식 코드

Occlusion Coherence: Detecting and Localizing Occluded Faces

https://github.com/google-research/google-research

공식 코드

ArtVLM: Attribute Recognition Through Vision-Based Prefix Language Modeling

https://github.com/google-research/simclr

공식 코드

A Simple Framework for Contrastive Learning of Visual Representations

https://github.com/guanjiyang/sac_jc

공식 코드

Sample Correlation for Fingerprinting Deep Face Recognition

https://github.com/guanzhenli/mvp-bench

공식 코드

MVP-Bench: Can Large Vision--Language Models Conduct Multi-level Visual Perception Like Humans?

https://github.com/gugarosa/mh_fine_tuning

공식 코드

Improving Pre-Trained Weights Through Meta-Heuristics Fine-Tuning

https://github.com/gugarosa/opf_distance

공식 코드

Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification

https://github.com/gugarosa/opfython

공식 코드

OPFython: A Python-Inspired Optimum-Path Forest Classifier

https://github.com/guliisgreat/orbit-2022-winner-method

공식 코드

Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022

https://github.com/gyh5421/unified_deep_clustering

공식 코드

Learning the Precise Feature for Cluster Assignment

https://github.com/gyhandy/Pose-Augmentation

공식 코드

Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition

https://github.com/gyhandy/humanoid-vision-engine

공식 코드

Contributions of Shape, Texture, and Color in Visual Recognition

https://github.com/haamoon/finding_common_object

공식 코드

Learning to Find Common Objects Across Few Image Collections

https://github.com/hadushhailu/daal-dml

공식 코드

DAAL: Density-Aware Adaptive Line Margin Loss for Multi-Modal Deep Metric Learning

https://github.com/haoning724/obbstacking

공식 코드

OBBStacking: An Ensemble Method for Remote Sensing Object Detection

https://github.com/harryqu123/lmc

공식 코드

LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition

https://github.com/hellozhuo/pidinet

공식 코드

Lightweight Pixel Difference Networks for Efficient Visual Representation Learning

https://github.com/hhx0320/asnn

공식 코드

Optimizing Spatio-Temporal Information Processing in Spiking Neural Networks via Unconstrained Leaky Integrate-and-Fire Neurons and Hybrid Coding

https://github.com/hkust-vgd/pointwise

공식 코드

Pointwise Convolutional Neural Networks

https://github.com/hosseinadeli/ocra

공식 코드

Recurrent Attention Models with Object-centric Capsule Representation for Multi-object Recognition

https://github.com/hskalena/exot

공식 코드

EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving Object

https://github.com/hsp-iit/prosthetic-grasping-simulation

공식 코드

Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis

https://github.com/htconquer/ddh

공식 코드

Deep Discrete Hashing with Self-supervised Pairwise Labels

https://github.com/htlsn/igan

공식 코드

One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network

https://github.com/huggingface/datasets

공식 코드

Datasets: A Community Library for Natural Language Processing

https://github.com/hustyyq/where-to-edit

공식 코드

Learning Where to Edit Vision Transformers

https://github.com/hy2mk/contextmix

공식 코드

ContextMix: A context-aware data augmentation method for industrial visual inspection systems

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.