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device_map Explained: Why model.to() Breaks Auto-Placed LLMs in Transformers
Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibration(ECCV 2022)
MOST: Multiple Object Localization with Self-Supervised Transformers for Object Discovery
Spotlight Talk on ViTOL: Vision Transformer for Weakly Supervised Object Localization at #CVPR-2022
Weakly Supervised Discriminative Feature Learning With State Information for Person Identification
The 3rd Place of Track-3: Weakly Supervised Object Localization
Learning a Weakly-Supervised Video Actor-Action Segmentation Model With a Wise Selection
Transformer Part 1: Tokenizer, Embedding, and Multihead Attention
Weakly Supervised Action Localization by Generative Attention Modeling
LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding (CVPR 2023)
Paper ID 70 - Re-Attention Transformer for Weakly Supervised Object Localization
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Last Updated: October 1, 2026
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Task Aware Weakly Supervised Object Localization With Transformer When you load a model with device_map set to auto, Accelerate scans your hardware and places every layer before the weights ... This talk describes our work in Authors: Hong-Xing Yu, Wei-Shi Zheng Description: Unsupervised learning of identity-discriminative visual feature is appealing in ... Achieve the 3rd place of Track 3 " Authors: Jie Chen, Zhiheng Li, Jiebo Luo, Chenliang Xu Description: We address In this video, I cover some basic components such as loading data, tokenizer, building embedding laters, and attention ... Learn all the ways Microsoft is a part of CVPR 2020: microsoft.com/en-us/research/event/cvpr-2020/ Video for our CVPR 2023 paper - LOCATE:
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