Workshop
ImageNet: Past, Present, and Future
Zeynep Akata · Lucas Beyer · Sanghyuk Chun · A. Sophia Koepke · Diane Larlus · Seong Joon Oh · Rafael Rezende · Sangdoo Yun · Xiaohua Zhai
Mon 13 Dec, 4 a.m. PST
Since its release in 2010, ImageNet has played an instrumental role in the development of deep learning architectures for computer vision, enabling neural networks to greatly outperform hand-crafted visual representations. ImageNet also quickly became the go-to benchmark for model architectures and training techniques which eventually reach far beyond image classification. Today’s models are getting close to “solving” the benchmark. Models trained on ImageNet have been used as strong initialization for numerous downstream tasks. The ImageNet dataset has even been used for tasks going way beyond its initial purpose of training classification model. It has been leveraged and reinvented for tasks such as few-shot learning, self-supervised learning and semi-supervised learning. Interesting re-creation of the ImageNet benchmark enables the evaluation of novel challenges like robustness, bias, or concept generalization. More accurate labels have been provided. About 10 years later, ImageNet symbolizes a decade of staggering advances in computer vision, deep learning, and artificial intelligence.
We believe now is a good time to discuss what’s next: Did we solve ImageNet? What are the main lessons learnt thanks to this benchmark? What should the next generation of ImageNet-like benchmarks encompass? Is language supervision a promising alternative? How can we reflect on the diverse requirements for good datasets and models, such as fairness, privacy, security, generalization, scale, and efficiency?
Schedule
Mon 4:00 a.m. - 4:30 a.m.
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Opening
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Opening presentation
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SlidesLive Video |
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Mon 4:30 a.m. - 5:00 a.m.
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Fairness and privacy aspects of ImageNet
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Talk
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SlidesLive Video |
Olga Russakovsky · Kaiyu Yang 🔗 |
Mon 5:00 a.m. - 5:30 a.m.
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OpenImages: One Dataset for Many Computer Vision Tasks
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Talk
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SlidesLive Video |
Vittorio Ferrari 🔗 |
Mon 5:30 a.m. - 6:00 a.m.
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Object recognition in machines and brains
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Talk
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SlidesLive Video |
Matthias Bethge 🔗 |
Mon 6:00 a.m. - 7:00 a.m.
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Live panel: The future of ImageNet
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Live panel
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SlidesLive Video |
Matthias Bethge · Vittorio Ferrari · Olga Russakovsky 🔗 |
Mon 7:30 a.m. - 7:45 a.m.
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Spotlight talk: ResNet strikes back: An improved training procedure in timm.
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Oral session
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link
SlidesLive Video |
Hugo Touvron 🔗 |
Mon 7:45 a.m. - 8:45 a.m.
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Poster session A ( Poster session ) > link | 🔗 |
Mon 8:45 a.m. - 9:15 a.m.
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Is ImageNet Solved? Evaluating Machine Accuracy
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Talk
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SlidesLive Video |
Becca Roelofs 🔗 |
Mon 9:15 a.m. - 9:45 a.m.
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From ImageNet to Image Classification
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Talk
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SlidesLive Video |
Shibani Santurkar 🔗 |
Mon 9:45 a.m. - 10:15 a.m.
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Are we done with ImageNet?
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Talk
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SlidesLive Video |
Alexander Kolesnikov 🔗 |
Mon 10:15 a.m. - 11:15 a.m.
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Live panel: Did we solve ImageNet?
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Live panel
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SlidesLive Video |
Shibani Santurkar · Alexander Kolesnikov · Becca Roelofs 🔗 |
Mon 11:45 a.m. - 12:15 p.m.
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Uncovering the Deep Unknowns of ImageNet Model: Challenges and Opportunties
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Talk
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SlidesLive Video |
Yixuan Li 🔗 |
Mon 12:15 p.m. - 12:45 p.m.
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ImageNet models from the trenches
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Talk
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SlidesLive Video |
Ross Wightman 🔗 |
Mon 12:45 p.m. - 1:15 p.m.
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Using ImageNet to Measure Robustness and Uncertainty
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Talk
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SlidesLive Video |
Dawn Song · Dan Hendrycks 🔗 |
Mon 1:15 p.m. - 2:15 p.m.
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Live panel: Perspectives on ImageNet.
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Live panel
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SlidesLive Video |
Dawn Song · Ross Wightman · Dan Hendrycks 🔗 |
Mon 2:30 p.m. - 3:00 p.m.
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ImageNets of "x": ImageNet's Infrastructural Impact
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Talk
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SlidesLive Video |
Emily Denton · Alex Hanna 🔗 |
Mon 3:00 p.m. - 3:30 p.m.
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Live panel: ImageNets of "x": ImageNet's Infrastructural Impact
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Live panel
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SlidesLive Video |
Emily Denton · Alex Hanna 🔗 |
Mon 3:45 p.m. - 4:00 p.m.
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Spotlight talk: Learning Background Invariance Improves Generalization and Robustness in Self Supervised Learning on ImageNet and Beyond
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Oral session
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link
SlidesLive Video |
Chaitanya Ryali 🔗 |
Mon 4:00 p.m. - 5:00 p.m.
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Poster session B ( Poster session ) > link | 🔗 |
Mon 5:00 p.m. - 5:15 p.m.
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Closing & awards
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Workshop closing
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SlidesLive Video |
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