id stringlengths 13 13 | question_zh stringlengths 4 240 | question_en stringlengths 6 1.47k | answer_zh stringlengths 1 1.08k | answer_en stringlengths 1 1.08k | answer_mask stringclasses 76
values | l1_zh stringclasses 7
values | l2_zh stringclasses 20
values | l3_zh stringclasses 52
values | l4_zh stringclasses 93
values | l1_en stringclasses 7
values | l2_en stringclasses 20
values | l3_en stringclasses 51
values | l4_en stringclasses 93
values | image imagewidth (px) 26 5.71k |
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sample_002801 | 这是什么植物？ | What plant is this? | 厄瓜多尔紫茄 | Solanum ecuadorense (Ecuadorian purple eggplant) | 细粒度-精细辨别 | 基础识别 | 生物/身体特征识别 | Fine-grained Discrimination | Basic Recognition | Biological / Anatomical Feature Recognition | ||||
sample_002802 | 这是什么品种的狗？ | What breed of dog is this? | 阿图瓦猎犬 | Artois Hound (Chien d'Artois) | 细粒度-精细辨别 | 基础识别 | 生物/身体特征识别 | Fine-grained Discrimination | Basic Recognition | Biological / Anatomical Feature Recognition | ||||
sample_002803 | 这是什么植物？ | What plant is this? | 火筒树 | Bandicoot Berry (Leea indica) | 细粒度-精细辨别 | 基础识别 | 生物/身体特征识别 | Fine-grained Discrimination | Basic Recognition | Biological / Anatomical Feature Recognition | ||||
sample_002804 | 检测出图中所有人的手、脚、腿，是否有生图带来的肢体数量异常。 | Detect whether there is an abnormal number of limbs (hands, feet, legs) for all people in the picture caused by AI image generation. | 图片最右侧白衣女生腰侧的手不属于白衣女生和中间的棕色上衣女生，明显是凭空生出的多余手臂，因此合照中多出了一只手 | The hand near the waist of the girl in white on the far right does not belong to either the girl in white or the girl in brown in the middle; it is clearly an extra arm generated out of nowhere, so there is an extra hand in the group photo. | 细粒度-精细辨别 | 基础识别 | 生物/身体特征识别 | Fine-grained Discrimination | Basic Recognition | Biological / Anatomical Feature Recognition | ||||
sample_002805 | 图中是什么昆虫？ | What insect is in the picture? | 委内瑞拉贵宾犬蛾 | Venezuelan poodle moth | 细粒度-精细辨别 | 基础识别 | 生物/身体特征识别 | Fine-grained Discrimination | Basic Recognition | Biological / Anatomical Feature Recognition | ||||
sample_002806 | 图中只有一个人，检测出图中这个人的手、脚、腿，是否有肢体数量异常 | There is only one person in the picture. Detect whether there is an abnormal number of limbs (hands, feet, legs) for this person. | 无异常 | No anomaly | 细粒度-精细辨别 | 基础识别 | 生物/身体特征识别 | Fine-grained Discrimination | Basic Recognition | Biological / Anatomical Feature Recognition | ||||
sample_002807 | 地上有几对黄黑相间的减速带？（默认都为成对出现） | How many pairs of yellow-and-black speed bumps are on the ground? (Default is that they all appear in pairs) | 8 | 8 | 粗粒度-语义识别 | 基础识别 | 视觉实体识别 | Semantic Recognition | Basic Recognition | Visual Object Recognition | ||||
sample_002808 | 图中一共出现了几个桃子片？ | How many peach slices appear in total in the picture? | 5 | 5 | 粗粒度-语义识别 | 基础识别 | 视觉实体识别 | Semantic Recognition | Basic Recognition | Visual Object Recognition | ||||
sample_002809 | 图中有几辆玩具车？ | How many toy cars are in the picture? | 12 | 12 | 粗粒度-语义识别 | 基础识别 | 视觉实体识别 | Semantic Recognition | Basic Recognition | Visual Object Recognition | ||||
sample_002810 | 图中有几块积木？ | How many building blocks are in the picture? | 48 | 48 | 粗粒度-语义识别 | 基础识别 | 视觉实体识别 | Semantic Recognition | Basic Recognition | Visual Object Recognition | ||||
sample_002811 | 图中共有几个草编的垫子 | How many straw woven mats in total are in the picture? | 5 | 5 | 粗粒度-语义识别 | 基础识别 | 视觉实体识别 | Semantic Recognition | Basic Recognition | Visual Object Recognition | ||||
sample_002812 | 图中的图形是由几个矩形构成? | How many rectangles make up the figure in the picture? | 2 | 2 | 粗粒度-语义识别 | 基础识别 | 抽象图案识别 | Semantic Recognition | Basic Recognition | Abstract Pattern Recognition | ||||
sample_002813 | 图中有几个正方形 | How many squares are in the picture? | 17 | 17 | 粗粒度-语义识别 | 基础识别 | 抽象图案识别 | Semantic Recognition | Basic Recognition | Abstract Pattern Recognition | ||||
sample_002814 | 图中有几个正方形 | How many squares are in the picture? | 7 | 7 | 粗粒度-语义识别 | 基础识别 | 抽象图案识别 | Semantic Recognition | Basic Recognition | Abstract Pattern Recognition | ||||
sample_002815 | 图中有几个完整的圆形 | How many complete circles are in the picture? | 9 | 9 | 粗粒度-语义识别 | 基础识别 | 抽象图案识别 | Semantic Recognition | Basic Recognition | Abstract Pattern Recognition | ||||
sample_002816 | 图中有几个完整的圆形？ | How many complete circles are in the picture? | 19 | 19 | 粗粒度-语义识别 | 基础识别 | 抽象图案识别 | Semantic Recognition | Basic Recognition | Abstract Pattern Recognition | ||||
sample_002817 | 图中有几个人将双手放在面部？ | How many people in the picture have both hands on their faces? | 4 | 4 | 粗粒度-语义识别 | 动作与交互 | 单体定格动作 | Semantic Recognition | Actions and Interactions | Single-Entity Actions in Still Images | ||||
sample_002818 | 图中有几个人举着手？ | How many people in the picture are raising their hands? | 6 | 6 | 粗粒度-语义识别 | 动作与交互 | 单体定格动作 | Semantic Recognition | Actions and Interactions | Single-Entity Actions in Still Images | ||||
sample_002819 | 图中有几个做出“劈叉”这个舞蹈动作的人？ | How many people in the picture are doing the dance move "splits"? | 11 | 11 | 粗粒度-语义识别 | 动作与交互 | 单体定格动作 | Semantic Recognition | Actions and Interactions | Single-Entity Actions in Still Images | ||||
sample_002820 | 图中有几个比剪刀手的人？ | How many people in the picture are making a peace / V-sign gesture? | 8 | 8 | 粗粒度-语义识别 | 动作与交互 | 单体定格动作 | Semantic Recognition | Actions and Interactions | Single-Entity Actions in Still Images | ||||
sample_002821 | 有几个人拍照做出点赞手势？ | How many people are making a thumbs-up gesture for the photo? | 3 | 3 | 粗粒度-语义识别 | 动作与交互 | 单体定格动作 | Semantic Recognition | Actions and Interactions | Single-Entity Actions in Still Images | ||||
sample_002822 | 图中条纹衣服的人在车顶上做什么 | What is the person in striped clothes doing on the roof of the car in the picture? | 单脚抬高站在车顶 | Standing on the car roof with one leg raised high | 粗粒度-语义识别 | 动作与交互 | 跨实体定格交互 | Semantic Recognition | Actions and Interactions | Inter-Entity Interactions in Still Images | ||||
sample_002823 | 哪几个人在相互比心 | Which people are making finger hearts with each other? | 左一、左二、左三 | First from left, second from left, third from left | 粗粒度-语义识别 | 动作与交互 | 跨实体定格交互 | Semantic Recognition | Actions and Interactions | Inter-Entity Interactions in Still Images | ||||
sample_002824 | 后方白衣女子手部动作是什么？ | What is the hand gesture/action of the woman in white in the back? | 搭在粉衣女子肩上 | Resting on the shoulder of the woman in pink | 粗粒度-语义识别 | 动作与交互 | 跨实体定格交互 | Semantic Recognition | Actions and Interactions | Inter-Entity Interactions in Still Images | ||||
sample_002825 | 图里发生了什么 | What happened in the picture? | 一个男子被两辆车夹在中间 | A man is caught/sandwiched between two cars | 粗粒度-语义识别 | 动作与交互 | 跨实体定格交互 | Semantic Recognition | Actions and Interactions | Inter-Entity Interactions in Still Images | ||||
sample_002826 | 图中的人在做什么？ | What are the people in the picture doing? | 两人同时挥拳打中了对方的脸，假装互殴 | Both people punched each other's faces simultaneously, pretending to fight each other | 粗粒度-语义识别 | 动作与交互 | 跨实体定格交互 | Semantic Recognition | Actions and Interactions | Inter-Entity Interactions in Still Images | ||||
sample_002827 | 有几扇窗开着？ | How many windows are open? | 8 | 8 | 粗粒度-语义识别 | 状态与属性 | 物理与阶段状态 | Semantic Recognition | States and Attributes | Physical and Stage-Related States | ||||
sample_002828 | 图中有几扇开着的柜门？ | How many cabinet doors are open in the picture? | 8 | 8 | 粗粒度-语义识别 | 状态与属性 | 物理与阶段状态 | Semantic Recognition | States and Attributes | Physical and Stage-Related States | ||||
sample_002829 | 图中有几扇窗开着？ | How many windows are open in the picture? | 2 | 2 | 粗粒度-语义识别 | 状态与属性 | 物理与阶段状态 | Semantic Recognition | States and Attributes | Physical and Stage-Related States | ||||
sample_002830 | 图中有几个不亮的小灯？ | How many unlit small lights are in the picture? | 5 | 5 | 粗粒度-语义识别 | 状态与属性 | 物理与阶段状态 | Semantic Recognition | States and Attributes | Physical and Stage-Related States | ||||
sample_002831 | 当前房间有几扇开着的窗户？ | How many open windows are in the current room? | 2 | 2 | 粗粒度-语义识别 | 状态与属性 | 物理与阶段状态 | Semantic Recognition | States and Attributes | Physical and Stage-Related States | ||||
sample_002832 | 图中有几辆警车？ | How many police cars are in the picture? | 2 | 2 | 粗粒度-语义识别 | 状态与属性 | 实体附带属性 | Semantic Recognition | States and Attributes | Additional Entity Attributes | ||||
sample_002833 | 有几辆消防车（能看到轮胎的均可计入） | How many fire trucks are there? (Any where tires are visible can be counted) | 5 | 5 | 粗粒度-语义识别 | 状态与属性 | 实体附带属性 | Semantic Recognition | States and Attributes | Additional Entity Attributes | ||||
sample_002834 | 图中有几名女童？ | How many young girls are in the picture? | 5 | 5 | 粗粒度-语义识别 | 状态与属性 | 实体附带属性 | Semantic Recognition | States and Attributes | Additional Entity Attributes | ||||
sample_002835 | 图中有几辆被车罩完全覆盖的车？ | How many cars are completely covered by car covers in the picture? | 2 | 2 | 粗粒度-语义识别 | 状态与属性 | 实体附带属性 | Semantic Recognition | States and Attributes | Additional Entity Attributes | ||||
sample_002836 | 图中有几辆用于挖土的车？ | How many vehicles used for digging/earthmoving are in the picture? | 8 | 8 | 粗粒度-语义识别 | 状态与属性 | 实体附带属性 | Semantic Recognition | States and Attributes | Additional Entity Attributes | ||||
sample_002837 | 图中有几个小孩在笑？ | How many children are smiling in the picture? | 1 | 1 | 粗粒度-语义识别 | 状态与属性 | 表情与微情绪 | Semantic Recognition | States and Attributes | Facial Expressions and Subtle Emotions | ||||
sample_002838 | 图中有几个人在哭泣，需要看到面部整体的表情 | How many people in the picture are crying? The overall facial expression needs to be visible. | 2 | 2 | 粗粒度-语义识别 | 状态与属性 | 表情与微情绪 | Semantic Recognition | States and Attributes | Facial Expressions and Subtle Emotions | ||||
sample_002839 | 图中有几个人在笑？ | How many people are smiling in the picture? | 1（最右侧穿浅灰色 T 恤、牛仔灯笼裤的小女孩） | 1 (The little girl on the far right wearing a light gray T-shirt and denim bloomers) | 粗粒度-语义识别 | 状态与属性 | 表情与微情绪 | Semantic Recognition | States and Attributes | Facial Expressions and Subtle Emotions | ||||
sample_002840 | 几个人在笑？（需要有明显笑容） | How many people are smiling? (Requires an obvious smile) | 3 | 3 | 粗粒度-语义识别 | 状态与属性 | 表情与微情绪 | Semantic Recognition | States and Attributes | Facial Expressions and Subtle Emotions | ||||
sample_002841 | 输出从左往右数，面部有明显笑容的人的序号 | Output the sequence numbers of people with obvious smiles on their faces, counting from left to right. | 2、3、4、7、8 | 2, 3, 4, 7, 8 | 粗粒度-语义识别 | 状态与属性 | 表情与微情绪 | Semantic Recognition | States and Attributes | Facial Expressions and Subtle Emotions | ||||
sample_002842 | 绿框里的鱼群原本是什么颜色？ | What was the original color of the school of fish in the green box? | 白色 | White | 粗粒度-语义识别 | 颜色感知 | 本征颜色推理 | Semantic Recognition | Color Perception | Intrinsic Color Reasoning | ||||
sample_002843 | 图中人物上衣本来是什么颜色？ | What was the original color of the person's top in the picture? | 灰色 | Gray | 粗粒度-语义识别 | 颜色感知 | 本征颜色推理 | Semantic Recognition | Color Perception | Intrinsic Color Reasoning | ||||
sample_002844 | 人物穿的裙子原本是什么颜色的？ | What was the original color of the skirt the person is wearing? | 蓝色 | Blue | 粗粒度-语义识别 | 颜色感知 | 本征颜色推理 | Semantic Recognition | Color Perception | Intrinsic Color Reasoning | ||||
sample_002845 | 画面左侧有纹路的墙体原本是什么颜色？ | What was the original color of the textured wall on the left side of the picture? | 白色 | White | 粗粒度-语义识别 | 颜色感知 | 本征颜色推理 | Semantic Recognition | Color Perception | Intrinsic Color Reasoning | ||||
sample_002846 | 在红色灯光照射下，人物穿的衣服原本是什么颜色 | Under the red light illumination, what was the original color of the clothes worn by the person? | 灰色 | Gray | 粗粒度-语义识别 | 颜色感知 | 本征颜色推理 | Semantic Recognition | Color Perception | Intrinsic Color Reasoning | ||||
sample_002847 | 每个选项覆盖一条分界线，墙和地面的分界线是哪个？ | Each option covers a boundary line. Which one is the boundary line between the wall and the ground? | C | C | 粗粒度-语义识别 | 语义关系 | 环境布局分割 | Semantic Recognition | Semantic Relations | Scene Layout Segmentation | ||||
sample_002848 | 图中有4条线，哪条线是矮墙和高墙的分界线？ | There are 4 lines in the picture. Which line is the boundary line between the low wall and the high wall? | 红色线 | Red line | 粗粒度-语义识别 | 语义关系 | 环境布局分割 | Semantic Recognition | Semantic Relations | Scene Layout Segmentation | ||||
sample_002849 | 图中有四条线，哪条线是天花板与柱子的分割线？ | There are four lines in the picture. Which line is the dividing line between the ceiling and the pillar? | 红色线 | Red line | 粗粒度-语义识别 | 语义关系 | 环境布局分割 | Semantic Recognition | Semantic Relations | Scene Layout Segmentation | ||||
sample_002850 | 图片红黄绿白蓝橙哪一条线是地面和夜空的分界线？ | Among the red, yellow, green, white, blue, and orange lines in the picture, which line is the boundary line between the ground and the night sky? | 黄线 | Yellow line | 粗粒度-语义识别 | 语义关系 | 环境布局分割 | Semantic Recognition | Semantic Relations | Scene Layout Segmentation | ||||
sample_002851 | 图中有6条线，哪条线是矮墙和地面的分界线？ | There are 6 lines in the picture. Which line is the boundary line between the low wall and the ground? | 绿线 | Green line | 粗粒度-语义识别 | 语义关系 | 环境布局分割 | Semantic Recognition | Semantic Relations | Scene Layout Segmentation | ||||
sample_002852 | 图中哪个选项可以打开啤酒瓶 | Which option in the picture can open a beer bottle? | C | C | 粗粒度-语义识别 | 语义关系 | 功能性语义关系 | Semantic Recognition | Semantic Relations | Functional Semantic Relations | ||||
sample_002853 | 墙上挂的工具有几个可以用来过滤沥干水分？ | How many of the tools hanging on the wall can be used to filter and drain water? | 4个 | 4 | 粗粒度-语义识别 | 语义关系 | 功能性语义关系 | Semantic Recognition | Semantic Relations | Functional Semantic Relations | ||||
sample_002854 | 图中工具是用来做什么的？ | What is the tool in the picture used for? | 用来清洁铲除缝隙污渍 | Used to clean and scrape off crevice/gap stains | 粗粒度-语义识别 | 语义关系 | 功能性语义关系 | Semantic Recognition | Semantic Relations | Functional Semantic Relations | ||||
sample_002855 | 图片中的工具是用来做什么的？ | What is the tool in the picture used for? | 砸坚果 | Cracking nuts | 粗粒度-语义识别 | 语义关系 | 功能性语义关系 | Semantic Recognition | Semantic Relations | Functional Semantic Relations | ||||
sample_002856 | 手上的物品是用来做什么的？ | What is the item in hand used for? | 易拉罐封口盖 | Can sealer lid / Beverage can cover | 粗粒度-语义识别 | 语义关系 | 功能性语义关系 | Semantic Recognition | Semantic Relations | Functional Semantic Relations | ||||
sample_002857 | 图中有一个白框和一个黄框，哪个框是开门按钮？ | There is a white box and a yellow box in the picture. Which box is the door opening button? | 黄框 | Yellow box | 定位 | 抽象概念定位 | 属性/功能定位 | Grounding | Abstract Concept Grounding | Attribute / Function-Based Grounding | ||||
sample_002858 | 什么颜色框里的英雄血量最少？ | In which color box does the hero have the least HP/health? | 黄色 | Yellow | 定位 | 抽象概念定位 | 属性/功能定位 | Grounding | Abstract Concept Grounding | Attribute / Function-Based Grounding | ||||
sample_002859 | 图中红黄蓝绿白哪个颜色方框中按键是打开全景影像功能的？ | Among the red, yellow, blue, green, and white square boxes in the picture, which color box contains the button to turn on the panoramic view function? | 红色框 | Red box | 定位 | 抽象概念定位 | 属性/功能定位 | Grounding | Abstract Concept Grounding | Attribute / Function-Based Grounding | ||||
sample_002860 | 什么颜色框里的英雄血量最少？ | In which color box does the hero have the least HP/health? | 红色框 | Red box | 定位 | 抽象概念定位 | 属性/功能定位 | Grounding | Abstract Concept Grounding | Attribute / Function-Based Grounding | ||||
sample_002861 | 图中哪个按键是打开空调内循环功能的？ | Which button in the picture turns on the air conditioning internal recirculation function? | F | F | 定位 | 抽象概念定位 | 属性/功能定位 | Grounding | Abstract Concept Grounding | Attribute / Function-Based Grounding | ||||
sample_002862 | 从鼠到鹰有几条食物链？ | How many food chains are there from mouse/rat to eagle? | 1 | 1 | 视觉追踪 | 线条追踪 | 线条观察 | 拓扑 | Visual Tracking | Line Tracing | Lines Observation | Topology | ||
sample_002863 | 白鸟任三郎想认识羽田秀吉，中间至少需要经过几个人？ | How many intermediate people at minimum does Ninzaburo Shiratori need to go through to get to know Shukichi Haneda? | 3 | 3 | 视觉追踪 | 线条追踪 | 线条观察 | 拓扑 | Visual Tracking | Line Tracing | Lines Observation | Topology | ||
sample_002864 | 从树皮到狼有几条食物链？ | How many food chains are there from tree bark to wolf? | 2 | 2 | 视觉追踪 | 线条追踪 | 线条观察 | 拓扑 | Visual Tracking | Line Tracing | Lines Observation | Topology | ||
sample_002865 | 席权的直接关系人有多少？（中间不隔人定义为直接关系） | How many direct contacts does Xi Quan have? (A direct relationship is defined as having no intermediate person in between) | 6 | 6 | 视觉追踪 | 线条追踪 | 线条观察 | 拓扑 | Visual Tracking | Line Tracing | Lines Observation | Topology | ||
sample_002866 | 排除山边，图中几人与靖子有间接关系？（中间只隔一个人的定义为间接关系） | Excluding Yamabe, how many people in the figure have an indirect relationship with Yasuko? (An indirect relationship is defined as having exactly one intermediate person in between) | 4 | 4 | 视觉追踪 | 线条追踪 | 线条观察 | 拓扑 | Visual Tracking | Line Tracing | Lines Observation | Topology | ||
sample_002867 | 图中有一个什么形状？ | What shape is in the picture? | 爱心形状 | Heart shape | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 点阵、线条干扰的复杂场景轮廓识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Contour Recognition in Complex Scenes with Dot-Pattern and Line Interference | ||
sample_002868 | 图片中央的图形是什么？ | What is the shape in the center of the picture? | 爱心 | Heart | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 点阵、线条干扰的复杂场景轮廓识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Contour Recognition in Complex Scenes with Dot-Pattern and Line Interference | ||
sample_002869 | 图片中央是什么数字 | What number is in the center of the picture? | 93 | 93 | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 点阵、线条干扰的复杂场景轮廓识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Contour Recognition in Complex Scenes with Dot-Pattern and Line Interference | ||
sample_002870 | 图片中是什么动物？ | What animal is in the picture? | 牛 | Ox / Cow | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 点阵、线条干扰的复杂场景轮廓识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Contour Recognition in Complex Scenes with Dot-Pattern and Line Interference | ||
sample_002871 | 图片中隐藏着什么物品？ | What item is hidden in the picture? | 点燃的蜡烛 | Lit candle | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 点阵、线条干扰的复杂场景轮廓识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Contour Recognition in Complex Scenes with Dot-Pattern and Line Interference | ||
sample_002872 | 找出与图案相匹配的阴影，回答选项即可。 | Find the shadow that matches the pattern. Please answer with the option only. | 4 | 4 | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 阴影轮廓提取与识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Shadow Contour Extraction and Recognition | ||
sample_002873 | 如图，左边图像对应几号阴影？ | As shown in the picture, which shadow number does the image on the left correspond to? | 2 | 2 | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 阴影轮廓提取与识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Shadow Contour Extraction and Recognition | ||
sample_002874 | 上方的图像对应哪一个选项的阴影？ | Which option's shadow does the image above correspond to? | A | A | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 阴影轮廓提取与识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Shadow Contour Extraction and Recognition | ||
sample_002875 | 下方哪一个阴影可以完全匹配上方的小马图案？ | Which shadow below can completely match the pony pattern above? | B | B | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 阴影轮廓提取与识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Shadow Contour Extraction and Recognition | ||
sample_002876 | 右侧影子中哪个影子能够对应左侧紫色怪兽？输出影子编号（右侧影子按从上到下、从左到右的顺序从1开始依次编号） | Which shadow on the right corresponds to the purple monster on the left? Output the shadow number (the shadows on the right are numbered sequentially starting from 1 from top to bottom, left to right). | 2 | 2 | 视觉追踪 | 轮廓识别 | 轮廓识人/识物 | 阴影轮廓提取与识别 | Visual Tracking | Contour Recognition | Person / Object Recognition from Contours | Shadow Contour Extraction and Recognition |
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