MO2.PA.1
Frozen Network Few-Shot Object Detection
Koshiro Nagano, Fumiaki Sato, Konicaminolta Inc., Japan; Ryo Hachiuma, NVIDIA, Japan; Kazuki Tsutsukawa, Konicaminolta Inc., Japan; Taiki Sekii, CyberAgent, Japan
Session:
MO2.PA: Machine Learning in Signal Processing 7 Poster
Track:
[ML] Machine Learning in Signal Processing
Location:
Poster Area A
Presentation Time:
Mon, 15 Sep, 10:00 - 11:30 Anchorage Time (UTC -8)
Session Chair:
Ambarish Natu, Australian Government
Presentation
Discussion
Resources
No resources available.
Session MO2.PA
MO2.PA.1: Frozen Network Few-Shot Object Detection
Koshiro Nagano, Fumiaki Sato, Konicaminolta Inc., Japan; Ryo Hachiuma, NVIDIA, Japan; Kazuki Tsutsukawa, Konicaminolta Inc., Japan; Taiki Sekii, CyberAgent, Japan
MO2.PA.2: Cluster Contrast for Unsupervised Visual Representation Learning
Nikolaos Giakoumoglou, Tania Stathaki, Imperial College London, United Kingdom
MO2.PA.3: DEFORMABLE SPHERICAL GEOMETRY TRANSFORMER FOR PANORAMIC SEMANTIC SEGMENTATION
Boyang Lan, Li Yang, Mai Xu, Lai Jiang, Yufeng Wang, Beihang University, China
MO2.PA.4: COMMON AND UNIQUE REPRESENTATION DEEP EMBEDDED CLUSTERING
Don Yates, Hakki Erhan Sevil, University of West Florida, United States; Arash Mahyari, Florida Institute for Human and Machine Cognition, United States
MO2.PA.5: REWARD-ADAPTATION: A NOVEL TEST-TIME ADAPTATION METHOD WITH REWARD MODEL
Tongxi Song, Shuai Wang, Rui Li, Tsinghua University, China
MO2.PA.6: Multi-class Smoothed Hinge Loss Function in Pre-training for Transfer Learning
Wonjik Kim, National Institute of Advanced Industrial Science and Technology, Japan; Masayuki Tanaka, Masatoshi Okutomi, Institute of Science Tokyo, Japan; Hirokazu Nosato, National Institute of Advanced Industrial Science and Technology, Japan
MO2.PA.7: HSBS: COMPREHENSIVE BOOSTING OF FACIAL EXPRESSION RECOGNITION VIA HIERARCHICAL SEMANTIC AND BATCH-WISE SIMILARITY
Zhiqing Wang, Jiabing Wang, Guihua Wen, SOUTH CHINA UNIVERSITY OF TECHNOLOGY, China
MO2.PA.8: GMOT-Mamba: Mamba-Based Model Prediction for Generic Multiple Object Tracking
Shashikant Verma, IIT Gandhinagar, India; Nicu Sebe, University of Trento, Italy, Italy; Shanmuganathan Raman, IIT Gandhinagar, India
MO2.PA.9: DIFFUSION PRETRAINING FOR GAIT RECOGNITION IN THE WILD
Wei Ming Neo, Nanyang Technological University, Singapore, Singapore; Koichi Shinoda, Institute of Science Tokyo, Japan; Tat-Jen Cham, Nanyang Technological University, Singapore, Singapore
MO2.PA.10: Edge-Guided Monocular Absolute Depth Estimation with Diffusion-Based Refinement
Bashayer Abdallah, Shan E Ahmed Raza, Victor Sanchez, University of Warwick, United Kingdom
MO2.PA.11: POLICY GRADIENT-BASED OPTIMAL SUBSET SELECTION FOR FEW-SHOT VISION-LANGUAGE LEARNING
Muhammad Khizer Ali, Manoranjan Paul, Charles Sturt University, Australia; Anwaar Ulhaq, Central Queensland University, Australia; Muhammad Haris Khan, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates; Quazi Mamun, Charles Sturt University, Australia
MO2.PA.12: LEARNING FROM PU DATA USING DISENTANGLED REPRESENTATIONS
Omar Zamzam, Haleh Akrami, Mahdi Soltanolkotabi, Richard Leahy, University of Southern California, United States
MO2.PA.13: Aggressive Rejection with Adaptive Gradient for Contaminated Data
Jungi Lee, Jungkwon Kim, Chi Zhang, Sangmin Kim, Kwangsun Yoo, Seok-Joo Byun, ELROILAB Inc., Korea (South)
MO2.PA.14: P-TAME: Explain Any Image Classifier with Trained Perturbations
Mariano V. Ntrougkas, Ethniko Kentro Ereunas & Technologikes Anaptyxes, Greece; Vasileios Mezaris, Ioannis Patras, Queen Mary University of London Faculty of Science and Engineering, United Kingdom of Great Britain and Northern Ireland
Contacts