Papers with Code 아카이브
Robotic Grasping
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
- 19
This task is composed of using Deep Learning to identify how best to grasp objects using robotic arms in different scenarios. This is a very complex task as it might involve dynamic environments and objects unknown to the network.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mees/AIS-Alexa-Robot
Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
https://github.com/mees/pickAndPlace-PR2
Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
https://github.com/mees/self-supervised-3D
Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics
https://github.com/mftnakrsu/DeepDream
https://github.com/mindspore-ai/models/tree/master/official/cv/inceptionv3
https://github.com/mindspore-courses/d2l-mindspore/tree/master/chapter_13_chapter_computer-vision
https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/inception_v3.py
https://github.com/minlee077/BARS
https://github.com/mjhucla/TF-mRNN
https://github.com/mjvakili/cassava_disease_classification
https://github.com/modelhub-ai/inception-v3
https://github.com/myarist/Rock-Paper-Scissors
https://github.com/mziad97/Frog-v-Giraffe
https://github.com/niranjana98/Image-Classification
https://github.com/open-mmlab/mmclassification
https://github.com/osmr/imgclsmob
https://github.com/otaheri/GrabNet
https://github.com/paperswithcode/model-index
https://github.com/pbaylies/stylegan-encoder
https://github.com/premthomas/keras-image-classification
https://github.com/puxinhe/im2txt_v3
https://github.com/pytorch/vision
https://github.com/qingchenkanlu/new_grasp
Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network
https://github.com/r-karthik/Detection-of-pests
https://github.com/rai-project/dlframework
https://github.com/raj-gupta1/Tomato-leaves-disease-Predictor
https://github.com/rhett-chen/graspness_implementation
Graspness Discovery in Clutters for Fast and Accurate Grasp Detection
https://github.com/rwightman/pytorch-image-models
https://github.com/sabeaussan/ROS_Unity
Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
https://github.com/shinpoi/pixiv_collector_old
https://github.com/smhall97/deep_dreaming_music
https://github.com/smrjan/robotic-vision
https://github.com/stefkim/stylegan-batik
https://github.com/stepjam/PyRep
Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-Stage Task
https://github.com/stoensin/IC
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.