WP1.L1.1
Learn by an Example Transformer for Domain Generalization in Video Object Segmentation
Islam Osman, Mohamed Shehata, University of British Columbia, Canada
Session:
WP1.L1: Predictable and Trustworthy Deep Learning Algorithms for Moving Object Detection for Challenging Environments Lecture
Track:
Special Sessions
Location:
Lecture Room 1
Presentation Time:
Wed, 30 Oct, 14:30 - 14:48 Gulf Standard Time (UTC +4)
Session Chair:
Thierry Bouwmans, La Rochelle Université, France
Session WP1.L1
WP1.L1.1: Learn by an Example Transformer for Domain Generalization in Video Object Segmentation
Islam Osman, Mohamed Shehata, University of British Columbia, Canada
WP1.L1.2: EDGE-GUIDED PIXEL LEVEL CONNECTED COMPONENT ASSISTED CAMOUFLAGED OBJECT DETECTION
Qingwang Wang, Xin Qu, Liyao Zhou, Pengcheng Jin, Chengbiao Fu, Tao Shen, Kunming University of Science and Technology, China
WP1.L1.3: LUMINATE: LINGUISTIC UNDERSTANDING AND MULTI-GRANULARITY INTERACTION FOR VIDEO OBJECT SEGMENTATION
Rahul Tekchandani, Ritik Maheshwari, GEC Ajmer, India; Praful Hambarde, IIT Ropar, India; Satya Narayan Tazi, GEC Ajmer, India; SANTOSH VIPPARTHI, INDIAN INSTITUTE OF TECHNOLOGY ROPAR, India; Subrahmanyam Murala, Trinity College Dublin, Ireland
WP1.L1.4: BI-DIRECTIONAL TRACKLET EMBEDDING FOR MULTI-OBJECT TRACKING
H. Çağrı Bilgi, A. Aydın Alatan, Middle East Technical University, Türkiye
WP1.L1.5: A CONFIDENCE-AWARE MATCHING STRATEGY FOR GENERALIZED MULTI-OBJECT TRACKING
Kyujin Shim, Jubi Hwang, Kangwook Ko, Changick Kim, Korea Advanced Institute of Science and Technology (KAIST), Korea, Republic of
Contacts