TP1.L3.2
CONTINUAL ROAD-SCENE SEMANTIC SEGMENTATION VIA FEATURE-ALIGNED SYMMETRIC MULTI-MODAL NETWORK
Francesco Barbato, Elena Camuffo, Simone Milani, Pietro Zanuttigh, University of Padova, Italy
Session:
TP1.L3: Perception Models in Visual AI Systems - II Lecture
Track:
Visual Artificial Intelligence
Location:
Capital Suite - 15
Presentation Time:
Tue, 29 Oct, 14:48 - 15:06 Gulf Standard Time (UTC +4)
Session Chair:
Simone Milani, University of Padova
Session TP1.L3
TP1.L3.1: MULTIMODAL-ENHANCED OBJECTNESS LEARNER FOR CORNER CASE DETECTION IN AUTONOMOUS DRIVING
Lixing Xiao, Ruixiao Shi, Xiaoyang Tang, Yi Zhou, Southeast University, China
TP1.L3.2: CONTINUAL ROAD-SCENE SEMANTIC SEGMENTATION VIA FEATURE-ALIGNED SYMMETRIC MULTI-MODAL NETWORK
Francesco Barbato, Elena Camuffo, Simone Milani, Pietro Zanuttigh, University of Padova, Italy
TP1.L3.3: OPEN WORLD OBJECT DETECTION VIA COOPERATIVE FOUNDATION MODELS FOR DRIVING SCENES
Sheng Luo, Yi Zhou, Southeast University, China
TP1.L3.4: POSE-INVARIANT LEARNING FOR EFFICIENT PERSON IDENTIFICATION FROM HYPERSPECTRAL HAND IMAGES
Keigo Kunikata, Amane Kashino, Yota Yamamoto, Yukinobu Taniguchi, Tokyo University of Science, Japan; Yoko Sogabe, Ayumi Matsumoto, Masaki Kitahara, NTT Corporation, Japan; Go Irie, Tokyo University of Science, Japan
TP1.L3.5: RFNET: REFINED FUSION THREE-BRANCH RGB-D SALIENT OBJECT DETECTION NETWORK
Kexuan Wang, University of Shanghai for Science and Technology, China; Chenhua Liu, Guangzhou Nansha Intelligent Photonic Sensing Research Institute, China; Huiguang Wei, Li Jing, Rongfu Zhang, University of Shanghai for Science and Technology, China
Contacts