#objectnet search results

Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work 10/N

stes_io's tweet image. Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work

10/N
stes_io's tweet image. Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work

10/N

#MachineLearning aims at making computers identify images of 3D objects like humans do. #ObjectNet by @MIT aims at achieving this through a dataset of training and testing images of objects in different orientations and surroundings. Read more on :bit.ly/38s8Vml

Techfest_IITB's tweet image. #MachineLearning aims at making computers identify images of 3D objects like humans do.
#ObjectNet by @MIT aims at achieving this through a dataset of training and testing images of objects in different orientations and surroundings.
Read more on :bit.ly/38s8Vml

But one of the hardest tasks in #OOD #generalization is defining rigorous test-sets. That's esp. true for natural images since nuisances are hard to define. #ObjectNet set the gold standard. The NICO dataset comes with rich context labels & could help: arxiv.org/abs/2204.08040

joungMax's tweet image. But one of the hardest tasks in #OOD #generalization is defining rigorous test-sets. That's esp. true for natural images since nuisances are hard to define. #ObjectNet set the gold standard. The NICO dataset comes with rich context labels & could help: arxiv.org/abs/2204.08040

Eager to check out #objectnet. That is the messy world dataset for images and objects. #computervision #imagenet #ai #wordnet objectnet.dev

RobertHoeijmak1's tweet image. Eager to check out  #objectnet. That is the messy world dataset for images and objects. #computervision #imagenet #ai #wordnet objectnet.dev

ObjectNet, a dataset compiled by MIT and IBM, demonstrates that there are - still - significant challenges and shortcomings related to "object detection / identification" by AI ... #ai #artificialintelligence #ObjectNet #objectreclnkd.in/djQ37bQ lnkd.in/dYCq78d


This @MIT_CSAIL object-recognition #dataset stumped the world’s best #ComputerVision models When leading object-detection models were tested on #ObjectNet, their accuracy rates fell from a high of 97% on #ImageNet to just 50-55% @GaryMarcus #DeepLearning news.mit.edu/2019/object-re…


But one of the hardest tasks in #OOD #generalization is defining rigorous test-sets. That's esp. true for natural images since nuisances are hard to define. #ObjectNet set the gold standard. The NICO dataset comes with rich context labels & could help: arxiv.org/abs/2204.08040

joungMax's tweet image. But one of the hardest tasks in #OOD #generalization is defining rigorous test-sets. That's esp. true for natural images since nuisances are hard to define. #ObjectNet set the gold standard. The NICO dataset comes with rich context labels & could help: arxiv.org/abs/2204.08040

Eager to check out #objectnet. That is the messy world dataset for images and objects. #computervision #imagenet #ai #wordnet objectnet.dev

RobertHoeijmak1's tweet image. Eager to check out  #objectnet. That is the messy world dataset for images and objects. #computervision #imagenet #ai #wordnet objectnet.dev

Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work 10/N

stes_io's tweet image. Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work

10/N
stes_io's tweet image. Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work

10/N

This @MIT_CSAIL object-recognition #dataset stumped the world’s best #ComputerVision models When leading object-detection models were tested on #ObjectNet, their accuracy rates fell from a high of 97% on #ImageNet to just 50-55% @GaryMarcus #DeepLearning news.mit.edu/2019/object-re…


ObjectNet, a dataset compiled by MIT and IBM, demonstrates that there are - still - significant challenges and shortcomings related to "object detection / identification" by AI ... #ai #artificialintelligence #ObjectNet #objectreclnkd.in/djQ37bQ lnkd.in/dYCq78d


#MachineLearning aims at making computers identify images of 3D objects like humans do. #ObjectNet by @MIT aims at achieving this through a dataset of training and testing images of objects in different orientations and surroundings. Read more on :bit.ly/38s8Vml

Techfest_IITB's tweet image. #MachineLearning aims at making computers identify images of 3D objects like humans do.
#ObjectNet by @MIT aims at achieving this through a dataset of training and testing images of objects in different orientations and surroundings.
Read more on :bit.ly/38s8Vml

#MachineLearning aims at making computers identify images of 3D objects like humans do. #ObjectNet by @MIT aims at achieving this through a dataset of training and testing images of objects in different orientations and surroundings. Read more on :bit.ly/38s8Vml

Techfest_IITB's tweet image. #MachineLearning aims at making computers identify images of 3D objects like humans do.
#ObjectNet by @MIT aims at achieving this through a dataset of training and testing images of objects in different orientations and surroundings.
Read more on :bit.ly/38s8Vml

Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work 10/N

stes_io's tweet image. Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work

10/N
stes_io's tweet image. Finally, what about more complex/“natural” domain shifts? We re-evaluate a ResNet-50 on #ObjectNet and find that our simple method does not improve results much in this case, motivating use of more involved unsupervised DA methods during robustness evaluation in future work

10/N

But one of the hardest tasks in #OOD #generalization is defining rigorous test-sets. That's esp. true for natural images since nuisances are hard to define. #ObjectNet set the gold standard. The NICO dataset comes with rich context labels & could help: arxiv.org/abs/2204.08040

joungMax's tweet image. But one of the hardest tasks in #OOD #generalization is defining rigorous test-sets. That's esp. true for natural images since nuisances are hard to define. #ObjectNet set the gold standard. The NICO dataset comes with rich context labels & could help: arxiv.org/abs/2204.08040

Eager to check out #objectnet. That is the messy world dataset for images and objects. #computervision #imagenet #ai #wordnet objectnet.dev

RobertHoeijmak1's tweet image. Eager to check out  #objectnet. That is the messy world dataset for images and objects. #computervision #imagenet #ai #wordnet objectnet.dev

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