MO4.L1.6

Deep Features based on Contrastive Fusion of Transformer and CNN for Semantic Segmentation

Margi Pandya, National Institute of Technology, Tiruchirappalli, United States; Tushar Sandhan, Indian Institute of Technology, Kanpur, India
Session:
MO4.L1: Innovative Approaches in Image and Signal Processing for Autonomous Vehicles: Integrating Incremental Learning and Explainable AI Lecture
Track:
Satellite Workshops
Location:
Dena'ina: Tikahtnu Ballroom A
Presentation Time:
Mon, 15 Sep, 17:15 - 17:24 Anchorage Time (UTC -9)
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Session MO4.L1
MO4.L1.1: GENERATIVE XR TRANSFER LEARNING FOR REAL TRAFFIC OBJECT DETECTION
Kuan-Ting Lai, Yan-Zhen Chen, Chi-Ting Liu, Ying-You Lin, Tzu-Hsin Liu, Kai-Ming Hu, Yi-Ju Hsiung, National Taipei University of Technology, Taiwan, Taiwan
MO4.L1.2: DYNAMIC OBJECT DETECTION FOR AUTONOMOUS VEHICLES USING MULTI-MODAL KNOWLEDGE DISTILLATION
Vishnudatta Thota, Tushar Sandhan, Indian Institute of Technology Kanpur, India
MO4.L1.3: Efficient Model-Based Purification Against Adversarial Attacks for LiDAR Segmentation
Alexandros Gkillas, AVISENSE.AI, Greece; Ioulia Kapsali, Industrial Systems Institute, Greece; Nikos Piperigkos, AVISENSE.AI, Greece; Aris Lalos, Industrial Systems Institute, Greece
MO4.L1.4: SEMANTIC PROPERTY MAPS FOR DRIVING APPLICATIONS
Marcus Greiff, Ray Zhang, Takeru Shirasawa, John Subosits, Toyota Research Institute, United States
MO4.L1.5: VIDEO LATENT STATE OPTIMIZATION IN SWITCHING MODELS FOR AUTONOMOUS AGENT TRAJECTORY PREDICTION
Abrham Shiferaw Alemaw, Pamela Zontone, Lucio Marcenaro, Carlo Regazzoni, University of Genoa, Italy
MO4.L1.6: Deep Features based on Contrastive Fusion of Transformer and CNN for Semantic Segmentation
Margi Pandya, National Institute of Technology, Tiruchirappalli, United States; Tushar Sandhan, Indian Institute of Technology, Kanpur, India
Contacts