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    [{"authors":null,"categories":null,"content":"Hello! I am Mingye Xie (谢铭烨). I am currently pursing Ph. D. degree in computer science and technology from Shanghai Jiao Tong University. I have received the B. Sc. degree and the M. Eng. degree in electronics and communications engineering from East China Normal University.\nMy main research topics are computer vision and machine learning. Specifically, I am currently doing research on Camouflage pattern generation, Generative Adversial Network (GAN), and Adversarial attack. I am also broadly interested in embedding systems programmingand model compressing.\n你好！我是谢铭烨，目前正在攻读上海交通大学的计算机科学与技术博士学位。本科与硕士均就读于华东师范大学。(在闵大荒的十几年求学时光…)\n我的研究领域包括伪装图案生成、生成对抗网络(GAN)、对抗攻击。我的研究兴趣还包括嵌入式软件开发和模型压缩与部署。\n","date":1713052800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1713052800,"objectID":"2525497d367e79493fd32b198b28f040","permalink":"","publishdate":"0001-01-01T00:00:00Z","relpermalink":"","section":"authors","summary":"Hello! I am Mingye Xie (谢铭烨). I am currently pursing Ph. D. degree in computer science and technology from Shanghai Jiao Tong University. I have","tags":null,"title":"Mingye Xie","type":"authors"},{"authors":["Jiacheng Ruan","Jingsheng Gao","Mingye Xie","Dahong Qian","Suncheng Xiang","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1713052800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1713052800,"objectID":"ce75975d6deec56de732ba49fc3fd7aa","permalink":"https://myronxie.github.io/publication/ruan2024idat/","publishdate":"2024-04-14T00:00:00Z","relpermalink":"/publication/ruan2024idat/","section":"publication","summary":"IEEE International Conference on Multimedia and Expo (ICME), 2024. (CCF-B)","tags":["Medical image segmentation","Light-weight model","mobile health"],"title":"iDAT: inverse Distillation Adapter-Tuning","type":"publication"},{"authors":["Suncheng Xiang","Hongwei Xu","Mingye Xie","Dahong Qian"],"categories":null,"content":"","date":1712188800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1712188800,"objectID":"34027263384c6d61e18f4ee99200223c","permalink":"https://myronxie.github.io/publication/xiang2024subface/","publishdate":"2024-04-04T00:00:00Z","relpermalink":"/publication/xiang2024subface/","section":"publication","summary":"Multimedia Tools and Applications, 2024. (CCF-C)","tags":["Face recognition","Embedding feature","Softmax approximation","Discriminability"],"title":"SubFace: learning with softmax approximation for face recognition","type":"publication"},{"authors":["Binjie Yan","Lin Xu","Zefang Yu","Mingye Xie","Wei Ran","Jingsheng Gao","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1709251200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1709251200,"objectID":"18e8d45626d0800136b59bd6401dc9e9","permalink":"https://myronxie.github.io/publication/yan2024learning/","publishdate":"2024-03-27T00:00:00Z","relpermalink":"/publication/yan2024learning/","section":"publication","summary":"Design, Automation and Test in Europe Conference 2024 (DATE). (CCF-B)","tags":["Floorplan","Reinforcement Leaning","Abnormal Detection","Placement Scorer"],"title":"Learning to Floorplan like Human Experts via Reinforcement Learning","type":"publication"},{"authors":["Zefang Yu","Mingye Xie","Jingsheng Gao","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1704067200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704067200,"objectID":"b2ee8a672e451e14af2661d17b4ddec8","permalink":"https://myronxie.github.io/publication/yu2024from/","publishdate":"2024-01-01T00:00:00Z","relpermalink":"/publication/yu2024from/","section":"publication","summary":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF-A)","tags":[],"title":"From Raw Video to Pedagogical Insights: A Unified Framework for Student Behavior Analysis","type":"publication"},{"authors":["Jingsheng Gao","Jiacheng Ruan","Suncheng Xiang","Zefang Yu","Ke Ji","Mingye Xie","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1704067200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704067200,"objectID":"aaabef15de319334f2abe21214e1e5cc","permalink":"https://myronxie.github.io/publication/gao2024lamm/","publishdate":"2024-01-01T00:00:00Z","relpermalink":"/publication/gao2024lamm/","section":"publication","summary":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF-A)","tags":[],"title":"LAMM: Label Alignment for Multi-Modal Prompt Learning","type":"publication"},{"authors":["Xin Xie","Dengquan Wu","Mingye Xie","Zixi Li"],"categories":null,"content":"","date":1701388800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1701388800,"objectID":"72fb12d85dcfeffa09df726475cf59d3","permalink":"https://myronxie.github.io/publication/xie2024ghostformer/","publishdate":"2024-01-01T00:00:00Z","relpermalink":"/publication/xie2024ghostformer/","section":"publication","summary":"Pattern Recognition, 2024. (CCF-B)","tags":["Object detection","Lightweight network design","Feature extraction","CNN-transformer"],"title":"GhostFormer: Efficiently amalgamated CNN-transformer architecture for object detection","type":"publication"},{"authors":["Mingye Xie","Zongwei Liu","Suncheng Xiang","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1689552000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1689552000,"objectID":"b7f064f08c88d52ba698b29ef516ed76","permalink":"https://myronxie.github.io/publication/xie2023editing/","publishdate":"2023-08-09T00:00:00Z","relpermalink":"/publication/xie2023editing/","section":"publication","summary":"Multimedia Tools and Applications, 2023. (CCF-C)","tags":["Scene editing","Synthetic data generation","Generative adversarial network (GAN)","Attribute editing"],"title":"Editing outdoor scenes with a large annotated synthetic dataset","type":"publication"},{"authors":["Jiacheng Ruan","Mingye Xie","Jingsheng Gao","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1685059200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1685059200,"objectID":"a00811afd3be60d59ed00e749c2a5284","permalink":"https://myronxie.github.io/publication/ruan2023ege/","publishdate":"2023-05-26T00:00:00Z","relpermalink":"/publication/ruan2023ege/","section":"publication","summary":"Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. (CCF-B)","tags":["Medical image segmentation","Light-weight model","mobile health"],"title":"EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation","type":"publication"},{"authors":["Jiacheng Ruan","Suncheng Xiang","Mingye Xie","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1666224000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1666224000,"objectID":"9a074d5c939900f5647d9faa0e2142ef","permalink":"https://myronxie.github.io/publication/ruan2022malunet/","publishdate":"2022-10-20T00:00:00Z","relpermalink":"/publication/ruan2022malunet/","section":"publication","summary":"International Conference on Bioinformatics and Biomedicine (BIBM), 2022. (CCF-B)","tags":["Light-weight model","Medical image segmentation","Attention mechanism","Mobile health"],"title":"MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation","type":"publication"},{"authors":null,"categories":["Personal"],"content":"[2024/01] I served as a reviewer of 2024 IEEE International Conference on Multimedia and Expo (ICME 2024).\n[2023/05] I served as a reviewer of 31st ACM International Conference on Multimedia (ACM MM 2023).\n[2022/08] I served as a reviewer of Expert Systems With Applications (ESWA).\n[2022/06] I served as a reviewer of 4th International Conference on Machine Learning for Cyber Security (ML4CS 2022).\n","date":1660003200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704790800,"objectID":"51e190430203a2d9c29421e8f0c4ef8a","permalink":"https://myronxie.github.io/post/2022-08-reviewer/","publishdate":"2022-08-09T00:00:00Z","relpermalink":"/post/2022-08-reviewer/","section":"post","summary":"(2024/01) I served as a reviewer of ICME 2024. (2023/05) I served as a reviewer of ACM MM 2023. (2022/08) I served as a reviewer of ESWA. (2022/06) I served as a reviewer of ML4CS 2022.","tags":["Personal"],"title":"📑 Reviewer Assignment","type":"post"},{"authors":["Mingye Xie","Suncheng Xiang","Feng Wang","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1646524800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1646524800,"objectID":"fc08f3ed02759b76a8a59d61b18836c1","permalink":"https://myronxie.github.io/publication/xie2022spatial/","publishdate":"2022-03-06T00:00:00Z","relpermalink":"/publication/xie2022spatial/","section":"publication","summary":"IEEE International Conference on Multimedia and Expo (ICME), 2022. (CCF-B, **Oral**)","tags":["Generative adversarial network (GAN)","Facial attribute manipulation","Attention mechanism"],"title":"Spatial Attention Guided Local Facial Attribute Editing","type":"publication"},{"authors":null,"categories":["Academic"],"content":"We first propose a mapping network to manipulate latent code which is effective for diverse situations, and design a spatial attention network to predict binary mask of certain attribute which encourages to only alter relevant region of images and suppress irrelevant changes.\nIn addition, we introduce a novel latent space into GAN inversion framework which achieves high reconstruction quality especially preserving identity features and retains ability to edit face attributes.\nSpatial thanks to Feng Wang for model building.\n","date":1646524800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1646524800,"objectID":"21f9457cd3a7c9c7da511b503d684a36","permalink":"https://myronxie.github.io/post/2022-03-face-editing/","publishdate":"2022-03-06T00:00:00Z","relpermalink":"/post/2022-03-face-editing/","section":"post","summary":"About face editing. Please refer to [Here](./publication/xie2022spatial/) for more information.","tags":["Academic"],"title":"🧐 One paper is accepted in ICME 2022!","type":"post"},{"authors":["Mingye Xie","Ting Liu","Yuzhuo Fu"],"categories":null,"content":"","date":1642809600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1642809600,"objectID":"fd87377041c5d18ea988a39a11380001","permalink":"https://myronxie.github.io/publication/xie2022gos/","publishdate":"2022-04-27T00:00:00Z","relpermalink":"/publication/xie2022gos/","section":"publication","summary":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022. (CCF-B)","tags":["Generative adversarial network (GAN)","Synthetic data generation","Scene editing"],"title":"GOS: A Large-Scale Annotated Outdoor Scene Synthetic Dataset","type":"publication"},{"authors":null,"categories":null,"content":"发明专利 (Patent) 基于视觉识别的精密轴尺寸测量方法、装置和系统\n国家发明专利（专利号：ZL201810042093.2）\n谢昕，谢铭烨，胡锋平，王伟如，江勋绎\n软件著作权 (Copyright of computer software) 非接触式触控屏控制软件\n软件著作权（登记号：2018SR522061）\n谢铭烨，金豫，等\n","date":1634256000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1634256000,"objectID":"ffe7f85b28a57a52802493118f09b96a","permalink":"https://myronxie.github.io/project/patent/","publishdate":"2021-10-15T00:00:00Z","relpermalink":"/project/patent/","section":"project","summary":"Click for more information...","tags":["Patent","Copyright of computer software"],"title":"Patents \u0026 Copyright of computer software","type":"project"},{"authors":null,"categories":["Academic"],"content":"We propose a large-scale, diverse synthetic dataset called “GOS dataset” generated based on video game, which contains fine-grained semantic annotations.\nDetailed information and samples about the dataset is available online at https://myronxie.github.io/GOS/.\n","date":1631750400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1645056000,"objectID":"23b9d0a06b370216bb2552f1740b08a3","permalink":"https://myronxie.github.io/post/2021-09-gos-dataset/","publishdate":"2021-09-16T00:00:00Z","relpermalink":"/post/2021-09-gos-dataset/","section":"post","summary":"Please refer to https://myronxie.github.io/GOS/ for more information.","tags":["Academic"],"title":"🏙️ GOS is accepted in ICASSP 2022!","type":"post"},{"authors":["Suncheng Xiang","Yuzhuo Fu","Mingye Xie","Zefang Yu","Ting Liu"],"categories":null,"content":"","date":1585526400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1585526400,"objectID":"a917c5b00efb67f46236e97218e95f67","permalink":"https://myronxie.github.io/publication/xiang2020unsupervised/","publishdate":"2020-03-30T00:00:00Z","relpermalink":"/publication/xiang2020unsupervised/","section":"publication","summary":"Multimedia Tools and Applications, 2020. (CCF-C)","tags":["re-ID","Unsupervised domain","Hierarchical clustering","TriHard loss"],"title":"Unsupervised person re-identification by hierarchical cluster and domain transfer","type":"publication"},{"authors":["Xin Xie","Songlin Ge","Fengping Hu","Mingye Xie","Nan Jiang"],"categories":null,"content":"","date":1550188800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1550188800,"objectID":"25968ed992d5a612f4c79ccab5658c2c","permalink":"https://myronxie.github.io/publication/xie2019improved/","publishdate":"2019-02-05T00:00:00Z","relpermalink":"/publication/xie2019improved/","section":"publication","summary":"Sentiment analysis is an important field of study in natural language processing. In the massive data and irregular data, sentiment classification with high accuracy is a major challenge in sentiment analysis. To address this problem, a novel maximum entropy-PLSA model is proposed. In this model, we first use the probabilistic latent semantic analysis to extract the seed emotion words from the Wikipedia and the training corpus. Then features are extracted from these seed emotion words, which are the input of the maximum entropy model for training the maximum entropy model. The test set is processed similarly into the maximum entropy model for emotional classification. Meanwhile, the training set and the test set are divided by the K-fold method. The maximum entropy classification based on probabilistic latent semantic analysis uses important emotional classification features to classify words, such as the relevance of words and parts of speech in the context, the relevance with degree adverbs, the similarity with the benchmark emotional words and so on. The experiments prove that the classification method proposed by this paper outperforms the compared methods.","tags":[],"title":"An improved algorithm for sentiment analysis based on maximum entropy","type":"publication"},{"authors":["Xin Xie","Songlin Ge","Mingye Xie","Fengping Hu","Nan Jiang"],"categories":null,"content":"","date":1550188800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1550188800,"objectID":"51630fb204e28bc1ed569e4e18a5b529","permalink":"https://myronxie.github.io/publication/xie2020improved/","publishdate":"2019-02-05T00:00:00Z","relpermalink":"/publication/xie2020improved/","section":"publication","summary":"In this paper, an improved sub-pixel edge detection algorithm combining coarse and precise location is proposed. The algorithm fully considers the 8-neighborhood pixel information and keeps the Roberts operator’s advantages of high location accuracy and fast speed. Meanwhile, it can effectively suppress noise and obtain better detection results. In order to solve the problem of low efficiency of the Zernike moment method in threshold selection, the Otsu’s method is introduced to achieve accurate sub-pixel edge location. The experimental results show that the proposed algorithm effectively improves the detection efficiency and the detection accuracy.","tags":[],"title":"Image matching algorithm of defects on navel orange surface based on compressed sensing","type":"publication"},{"authors":[],"categories":[],"content":"Create slides in Markdown with Hugo Blox Builder Hugo Blox Builder | Documentation\nFeatures Efficiently write slides in Markdown 3-in-1: Create, Present, and Publish your slides Supports speaker notes Mobile friendly slides Controls Next: Right Arrow or Space Previous: Left Arrow Start: Home Finish: End Overview: Esc Speaker notes: S Fullscreen: F Zoom: Alt + Click PDF Export Code Highlighting Inline code: variable\nCode block:\nporridge = \u0026#34;blueberry\u0026#34; if porridge == \u0026#34;blueberry\u0026#34;: print(\u0026#34;Eating...\u0026#34;) Math In-line math: $x + y = z$\nBlock math:\n$$ f\\left( x \\right) = ;\\frac{{2\\left( {x + 4} \\right)\\left( {x - 4} \\right)}}{{\\left( {x + 4} \\right)\\left( {x + 1} \\right)}} $$\nFragments Make content appear incrementally\n{{% fragment %}} One {{% /fragment %}} {{% fragment %}} **Two** {{% /fragment %}} {{% fragment %}} Three {{% /fragment %}} Press Space to play!\nOne Two Three A fragment can accept two optional parameters:\nclass: use a custom style (requires definition in custom CSS) weight: sets the order in which a fragment appears Speaker Notes Add speaker notes to your presentation\n{{% speaker_note %}} - Only the speaker can read these notes - Press `S` key to view {{% /speaker_note %}} Press the S key to view the speaker notes!\nOnly the speaker can read these notes Press S key to view Themes black: Black background, white text, blue links (default) white: White background, black text, blue links league: Gray background, white text, blue links beige: Beige background, dark text, brown links sky: Blue background, thin dark text, blue links night: Black background, thick white text, orange links serif: Cappuccino background, gray text, brown links simple: White background, black text, blue links solarized: Cream-colored background, dark green text, blue links Custom Slide Customize the slide style and background\n{{\u0026lt; slide background-image=\u0026#34;/media/boards.jpg\u0026#34; \u0026gt;}} {{\u0026lt; slide background-color=\u0026#34;#0000FF\u0026#34; \u0026gt;}} {{\u0026lt; slide class=\u0026#34;my-style\u0026#34; \u0026gt;}} Custom CSS Example Let’s make headers navy colored.\nCreate assets/css/reveal_custom.css with:\n.reveal section h1, .reveal section h2, .reveal section h3 { color: navy; } Questions? Ask\nDocumentation\n","date":1549324800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1549324800,"objectID":"0e6de1a61aa83269ff13324f3167c1a9","permalink":"https://myronxie.github.io/slides/example/","publishdate":"2019-02-05T00:00:00Z","relpermalink":"/slides/example/","section":"slides","summary":"An introduction to using Hugo Blox Builder's Slides feature.","tags":[],"title":"Slides","type":"slides"},{"authors":null,"categories":null,"content":"Research and Design of Multi-rotor UAV Sensor System Based on Pixhawk (Master Thesis)\nIn recent years, multi-rotor UAVs have shown great application value in the fields of aerial photography, power inspection, and agricultural plant protection due to their simple structure, convenient use and easy maintenance. With the continuous investment of commercial companies, research institutes and open source communities, the technology related to multi-rotor drones has developed vigorously.\nThe sensor system, as part of a multi-rotor drone, continuously provides reliable sensor raw data for the drone. The sensor data is finally converted into state information such as flight attitude and flight position of the drone through various algorithms within the system, which provides a basis for the multi-rotor UAV to achieve autonomous control. This paper uses the Pixhawk open source flight control system, based on the self-designed and built flight control software and hardware platform, the following research and design of the multi-rotor UAV sensor system:\nThe selection of sensor hardware was studied and evaluated. By comparing and verifying the performance parameters of each sensor, the MEMS sensor selection suitable for multi-rotor UAVs was selected. Research and implementation of sensor data processing algorithms. By analyzing the sensor error source and error type, the corresponding error model is established, and data processing methods such as data calibration processing, temperature compensation processing and data filtering processing are introduced according to this model to reduce the correlation error to the sensor data. The sensor data fusion algorithm and the UAV attitude calculation algorithm are studied and implemented. The multi-sensor fusion mechanism avoids the impact of a single sensor failure on the sensor system. Different types of sensor information are fused by introducing corresponding complementary filtering algorithms to reduce the error that occurs when the UAV attitude is solved. Through the above research and design, the sensor system can obtain more accurate and stable sensor raw data, which enables the flight control system to solve more accurate attitude information, and finally make the multi-rotor drone maintain a more stable flight.\n","date":1548892800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1548892800,"objectID":"4c5695742822dc2fb29d30d3392ae27f","permalink":"https://myronxie.github.io/project/master-thesis/","publishdate":"2019-01-31T00:00:00Z","relpermalink":"/project/master-thesis/","section":"project","summary":"Research and Design of Multi-rotor UAV Sensor System Based on Pixhawk","tags":["Thesis"],"title":"Master Thesis","type":"project"},{"authors":null,"categories":null,"content":"From Sep 2017 to Oct 2018.\nParticipate in the writing and testing of multi-rotor UAV accompanying computer embedded control software. Accompanying the computer using STM32F3 as the main control chip, its main functions are: controlling the onboard landing gear to carry out the retracting operation smoothly; controlling the power state of the onboard smart battery, and real-time collection of battery voltage, current, power and other related information; establishment Two-way communication with the drone’s onboard flight controller, receiving control signals to control the landing gear and smart battery, and sending the status information of the onboard equipment.\nParticipate in the writing and testing of the software and hardware of the multi-rotor UAV flight controller. The flight control software is written in a Unix-like environment. The main tasks include: Responsible for the driver writing and testing of UAV airborne sensors; research and optimize sensor data acquisition algorithms, processing algorithms and fusion algorithms, improve the stability of UAV attitude calculation; test flight controller hardware circuit boards Reliability, and make suggestions for improvement based on the problems encountered.\nAssist in the completion of other embedded-related projects within the company: a smart car that can run on a preset route through a remote control handle and take pictures of the goods on the shelf; monitor the vibration of the vibration state of each mechanical part of the drone through multiple accelerometers Recorder etc.\n","date":1539561600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1539561600,"objectID":"3f16f110ee75eb68b69cc33e5439fee9","permalink":"https://myronxie.github.io/project/clobotics/","publishdate":"2018-10-15T00:00:00Z","relpermalink":"/project/clobotics/","section":"project","summary":"As Embedded Software Assistant from Sep 2017 to Oct 2018.","tags":["Internship"],"title":"Internship in Clobotics","type":"project"}]