With the rapid development of artificial intelligence, compositional zero-shot learning (CZSL) can generalize unseen compositions by learning prior knowledge of seen attributes and object compositions during training. Although existing composition-based and relationship-based methods show great potential for ...
is adopted to utilize unlabeled test examples to alleviate the low-resource learning problem. Experiments on two widely-used zero-shot compositional learning (ZSCL) benchmarks have demonstrated the effectiveness of the model compared with recent approaches on both conventional and generalized ZSCL setting...
BSD-3-Clause license Compositional Soft Prompting (CSP) Compositional soft prompting (CSP), a parameter-efficient learning technique to improve the zero-shot compositionality of large-scale pretrained vision-language models (VLMs) without the overhead of fine-tuning the entire model. ...
“Locality and Compositionality In Zero-Shot Learning,” (opens in new tab) which was accepted to the eighth International Conference on Learning Representations (ICLR2020) (opens in new tab), we demonstrate that representations that focus on compositionality and locality are better at zero-...
Beyond Seen Primitive Concepts and Attribute-Object Compositional Learning Nirat Saini Khoi Pham Abhinav Shrivastava University of Maryland, College Park Abstract Learning from seen attribute-object pairs to general- ize to unseen compositions has been studied extensively in Comp...
Code for the paper Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning, ICCV 2023. Hanjae Kim, Jiyoung Lee, Seongheon Park, Kwanghoon Sohn Installation Please create conda environment and install dependencies following the below steps. conda env create --file environment.yml ...
论文名称:A Causal View of Compositional Zero-Shot Recognition 来自NVIDIA的作品,今年NIPS的spotlight,再一次让人看到了Causality,特别是intervention在传统CV领域带来的新路子。 首先我们先来分析一下标题, A causal view代表了他与传统工作不同的地方,以因果为工具,我们可以避免NN带来严重的spurious correlation和泛化...
Zero-Shot Learning—A Comprehensive Eval- uation of the Good, the Bad and the Ugly. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019. [67] Yongqin Xian, Bernt Schiele, and Zeynep Akata. Zero-Shot Learning — The Good, the Bad and the Ugly...
2021年CLIP模型发表,推动了zero-shot图像分类、文本-图像跨模态检索和文生图等领域的蓬勃发展。尽管展示出了显著能力,CLIP在compositional understanding方面有明显局限,难以捕捉图文在关系、动作、属性等方面的组合语义。比如CLIP难以区分由相同词汇组成但词汇顺序不同的标题, 如Figure 2[1]举例,CLIP对狗和猫的相对位置关...
Not only does this allow us to generalize to paths unseen at training time, but also, with a single high-capacity RNN, to predict new relation types not seen when the compositional model was trained (zero-shot learning). We assemble a new dataset of over 52M relational triples, and show...