Zero-shot recognition via structured prediction. In ECCV (2016).Z. Zhang and V. Saligrama. Zero-shot recognition via struc- tured prediction. In Proc. European Conf. on Computer Vi- sion, pages 533-548. Springer, 2016.Z. Zhang and V. Saligrama. Zero-shot recognition via structured pre-...
Zero-Shot Recognition via Structured Prediction Ziming Zhang(B) and Venkatesh Saligrama Department of Electrical and Computer Engineering, Boston University, Boston, USA {zzhang14,srv}@bu.edu Abstract. We develop a novel method for zero shot learning (ZSL) based on test-time adaptation of ...
Semantically Consistent Regularization for Zero-Shot Recognition Abstract 这篇论文主要对Zero-shot learning(ZSL)中语义空间的作用进行讨论。根据监督方式的不同,作者对以往方法的有效性进行了分析。一种是对语义空间进行单独地学习,另一种是通过训练类的解释来监督语义的子空间。前者可以对语义的整个空间进行约束,但缺...
2019_Progressive Ensemble Networks for Zero-Shot Recognition 2019_CVPR_渐进式标注unseen样本训练_投影到多个空间并集成_利用二次型标准化求解投影矩阵 选择K 个投影空间, 分别用 MLP 进行学习, 集成多个空间投影结果来进行相似度比较. 集成方法中用了二次型标准化方法进行求解集成结果. 后续还采用了半监督方法, ...
我们考虑 zero-shot recognition 的问题:学习一个类别的视觉分类器,并且不用 training data,仅仅依赖于 类别的单词映射(the word embedding of the category)及其与其他类别的关系(its relationship to other categories),但是会提供 visual data。处理这种不熟悉的或者新颖的类别,从已有的类别中进行知识的迁移是成功的...
MAFW Most implemented papers Most implementedSocialLatestNo code EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression Recognition nickyfot/emoclip• •25 Oct 2023 To test this, we evaluate using zero-shot classification of the model trained on sample-level descriptions on four...
论文名称:A causal view of compositional zero-shot recognition 原文作者:Yuval Atzmon 内容提要 人们很容易识别新的视觉类别,这些视觉类别是已知组件的新组合。因为新组合的长尾支配着分布,所以这种组合泛化能力对于在视觉和语言等现实世界中的学习非常重要。不幸的是,学习系统很难与组成概括相结合,因为它们通常建立在...
There have been tremendous strides in visual recognition over the past few years owing to the prosperity of deep learning [1], [2], [3], [4], [5], [6]. Despite the remarkable advances, state-of-the-art approaches in deep learning require a large quantity of annotated training samples...
• A simple yet effective convolutional prototype learning (CPL) framework is proposed for zero-shot recognition task. • CPL can facilitate the effective transferring of the learned knowledge from the source domain to the unseen target domain. • The generated prototypes are more discriminative ...
Multimodality helps unimodality: Crossmodal few-shot learning with multimodal models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 19325–19337, 2023.@将门创投 让创新获得认可 如果喜欢,别忘了赞同、关注、分享三连哦!~笔芯...