--- title: 'PaperV2 FeedBack' disqus: hackmd --- PaperV2 FeedBack === [TOC] ## Reviewer2 ## Reviewer3 ### Question1 You mentioned that some of tools like DarkLabel cannot track more than 100 objects in one frame (Fig10). What is your performance in that kind of frame? What is the FPS? ### Answer1 ![](https://i.imgur.com/OAI95iS.jpg) Fig1. NTUT_Vott label more than 100 target ![](https://i.imgur.com/Qsnwbso.jpg) Fig2. NTUT_Vott label more than 100 target when tracking ![](https://i.imgur.com/yumB8BI.png) Fig3. NTUT_Vott label more than 100 target performance in log ### Question2 I think it is not clear how your tool is used for labeling human actions? ### Answer2 ![](https://i.imgur.com/gMIIYqh.jpg) NTUT_Vott label human run action ![](https://i.imgur.com/wholzHe.png) NTUT_Vott label human run action in json --- ###### tags: `aboutPaper`
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VoTT NTUT README(ubuntu 18.04)

# README.md 來源

1/21/2024
For VoTT_NTUT_WIN10_repo ReadMe

NTUT VoTT Main Features of NTUT VoTT NTUT_VoTT tool is a modified version of Microsoft VoTT (based on Version: V2.2.0) open-source labeling software. It has the following new features: Automatic tracking after labeling, to reduce the tedious work of re-labeling each frame Multi-core tracking Track FPS for different scenarios :::info The below video shows NTUT VoTT how to save your time for labeling objects, you don't need to label those objects each frame, and this tool supports multi-core tracking which can speed up while you tracking more objects. :::

12/28/2023
For VoTT_NTUT_WIN10_repo ReadMe

[TOC] NTUT VoTT Main Features of NTUT VoTT NTUT_VoTT tool is a modified version of Microsoft VoTT (based on Version: V2.2.0) open-source labeling software. It has the following new features: Automatic tracking after labeling, to reduce the tedious work of re-labeling each frame Multi-core tracking Track FPS for different scenarios :::info

12/14/2022
論文方向

論文方向 [TOC] 1. 學分規劃 ::: info 由於在職碩士規定修業年限最低為2.5年,若要兩年畢業必須要發表一篇conference paper 如果依照正常流程規劃,在申請學位考試必須在二下修完所有學分,目前學分進度如下 ::: 二下：

7/11/2022
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