IVMSP-L3.5
FEATURE-CONSTRAINED AND ATTENTION-CONDITIONED DISTILLATION LEARNING FOR VISUAL ANOMALY DETECTION
Shuo Zhang, Jing Liu, East China Normal University, China
Session:
IVMSP-L3: Quality assessment and anomaly detection Lecture
Track:
Image, Video, and Multidimensional Signal Processing
Location:
Room 205A
Presentation Time:
Tue, 16 Apr, 17:50 - 18:10 (UTC +9)
Session Chair:
Han Yu, Nanyang Technological University
Session IVMSP-L3
IVMSP-L3.1: A crowdsourcing approach to video quality assessment
Babak Naderi, Ross Cutler, Microsoft, United States of America
IVMSP-L3.2: A Reduced-Reference Quality Assessment Metric for Textured Mesh Digital Humans
Zicheng Zhang, Yingjie Zhou, Chunyi Li, Kang Fu, Wei Sun, Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Shanghai Jiaotong University, China
IVMSP-L3.3: Image Aesthetics Assessment via Learnable Queries
Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen, Nanyang Technological University, Singapore; Peiran Ren, Alibaba Group, China; Han Yu, Nanyang Technological University, Singapore
IVMSP-L3.4: ZE-FESG: A ZERO-SHOT FEATURE EXTRACTION METHOD BASED ON SEMANTIC GUIDANCE FOR NO-REFERENCE VIDEO QUALITY ASSESSMENT
Yachun Mi, Yu Li, Yan Shu, Shaohui Liu, Harbin Institute of Technology, China
IVMSP-L3.5: FEATURE-CONSTRAINED AND ATTENTION-CONDITIONED DISTILLATION LEARNING FOR VISUAL ANOMALY DETECTION
Shuo Zhang, Jing Liu, East China Normal University, China
IVMSP-L3.6: CAGEN: CONTROLLABLE ANOMALY GENERATOR USING DIFFUSION MODEL
Bolin Jiang, Yuqiu Xie, Tsinghua Shenzhen International Graduate School, China; Jiawei Li, Huawei Manufacturing, China; Naiqi Li, Yong Jiang, Shu-Tao Xia, Tsinghua Shenzhen International Graduate School, China
Contacts