Our comparative experimental results on two benchmark datasets for image-text classification, CrisisMMD and UPMC Food-101, show that our proposed model outperforms other classification methods and even state-of-the-art (SOTA) multimodal classification methods. Meanwhile, the effectivene...
The results show that CMA-CLIP outperforms the pre-trained and fine-tuned CLIP by an average of 11.9% in recall at the same level of precision on the MRWPA dataset for multi-task classification. It also surpasses the state-of-the-art method on Fashion-Gen Dataset by 5.5% in accuracy ...
Masked Region Classification-KLDivergence(MRC-kl):除了对MASK region计算分类label,还可以计算UNITER与R-CNN对MASK region的分布差异,我们希望UNITER的region分布要尽可能接近R-CNN的region分布,loss使用KL散度。 3. ITM(Image Text Match, 图文是否一致) 对输入的Image-TextPair随机替换Image或者Text,最后预测输入的Im...
I am a Principal Researcher at Microsoft Cloud & AI and focus on large-scale multimodal representation learning recently. I have broad research interest, includingcomputer vision, e.g. image classification and object detection, and vision-language intelligence, e.g. vision-language pretraining and v...
2)Masked Region Classification (MRC)MRC 学习预测每个掩蔽区域的对象语义类.我们首先将屏蔽区域 v(i)min 的 Transformer 输出馈送到一个 FC 层来预测 Kobject 类的分数,它进一步通过一个 softmax 函数被转换为归一化分布 gθ(v(i)m)∈RK。请注意,没有真实标签,因为未提供对象类别。因此,我们使用 Faster R...
对于image-text embedding learning,作者提出了 cross-modal projection matching (CMPM) loss 和 cross-modal projection classification (CMPC) loss。前者最小化两个模态特征投影分布的KL散度;后者基于norm-softmax损失,对模态A在模态B上的投影特征进行分类,进一步增强模态之间的契合度。
Text and image classificationCustoms classification is an essential international procedure to import cross-border goods traded by various companies and individuals. Proper classification of such goods with high efficiency in light of the rapidly increasing amount of international trade is still challenging....
python run.py image-classification ./sample_image/pic1.jpg python run.py image-classification ./sample_image For image classification, used pretrained MobileNetV3-small and added Linear layer for final purpose. Joke-Generation Using any available LLM (like GPT-2 or similar): Train the model : ...
关键词: automatic image annotation dual-random ensemble learning image to text translation multi-label classification 会议名称: International Conference on Intelligent Computing 会议时间: 08/18/2010 主办单位: Springer, Berlin, Heidelberg 被引量: 5 ...
classification tasks. Thesoftware toolkitis also released to ease the process to onboad new models. It will be hosted as a challenge at theCV in the Wild Workshop @ ECCV 2022. We hope our benchmark and toolkit can encourage the community to solve the challenge of image classification in ...