large-vocabulary classifier中存在很多noisy logits img 研究内容 tree:将category之间的relation作为先验知识,构建一个classification tree,将fine-grained classes聚类得到coarser parent classes(数量少,noisy logits更少,可以抑制fine-grained class中的noisy logits) forest:由于构造parent class的方式不唯一,本文构建了多...
We aim to enable this new research direction by designing and collecting LVIS (pronounced ‘el-vis’)—a benchmark dataset for research on Large Vocabulary Instance Segmentation. We are collecting instance segmentation masks for more than 1000 entry-level object categories (see Fig.1). When comple...
LV-VIS is a dataset/benchmark for Open-Vocabulary Video Instance Segmentation. It contains a total of 4,828 videos with pixel-level segmentation masks for 26,099 objects from 1,196 unique categories. LV-VIS is licensed under aCC BY-NC-SA 4.0License. The data of LV-VIS is released for ...
这个网络将上述得到的 coarse attention maps,以及原图作为输入,得到最终概念级别的分割结果; 总体的流程图如下: 下面分别详细的介绍下对应的每一个模块: 1. Embedding Network: 作者在 Stock-18K dataset 上进行了训练,该数据集包含 6 million images,每一个图像都对应有标注的 tags,有 18K vocabulary。 Word Embe...
Title: Jurassic-1: Technical details and evaluation model family: GPT date created: 2021-09-01 organization: AI21 innovation: The Jurassic-1 model's primary innovation in the context of Large Language Models is its enhanced tokenization efficiency, achieved through a larger 256K vocabulary SentenceP...
Abstract Deep learning-based markerless tracking has revolutionized studies of animal behavior. Yet the generalizability of trained models tends to be limited, as new training data typically needs to be generated manually for each setup or visual environment. With each model trained from scratch, resea...
^https://openaccess.thecvf.com/content/CVPR2022/papers/Huynh_Open-Vocabulary_Instance_Segmentation_via_Robust_Cross-Modal_Pseudo-Labeling_CVPR_2022_paper.pdf ^https://arxiv.org/abs/2208.08984 ^https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Grounded_Language-Image_Pre-Training_CVPR_2022...
The text responses are obtained from y˜txt by applying a linear classifier to pre- dict the next words in the vocabulary. In LISA, a special token [SEG] is appended in the vo- cabulary to activate the segmentation ability of MLLM. The model learns to pred...
Additionally, based on SAM, Open-Vocabulary SAM [23] combines SAM with CLIP to enable SAM to output object categories. GLEE [24] uses the feature output by the large language model as a prompt for SAM to guide segmentation results. In multimodal fine-tuning for language tasks, LLaVA [25]...
Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning The framework of SongCi and studied large-vocabulary, multi-center datasets. Updates: 05/06/2024: We are working on refining the code updates for the SongCi model. Installation: Pre-requisites: python 3....