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ORCID18th ECCV Workshops 2024: Milan, Italy - Part XI
- Alessio Del Bue, Cristian Canton, Jordi Pont-Tuset, Tatiana Tommasi:
Computer Vision - ECCV 2024 Workshops - Milan, Italy, September 29-October 4, 2024, Proceedings, Part XI. Lecture Notes in Computer Science 15633, Springer 2025, ISBN 978-3-031-91978-7 - Mona Sheikh Zeinoddin, Chiara Lena, Jiongqi Qu, Luca Carlini, Mattia Magro, Seunghoi Kim, Elena De Momi, Sophia Bano
, Matthew Grech-Sollars, Evangelos B. Mazomenos, Daniel C. Alexander, Danail Stoyanov, Matthew J. Clarkson, Mobarakol Islam:
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation Model. 1-11 - Tao Huang, Xiaohuan Pei, Shan You, Fei Wang, Chen Qian, Chang Xu:
LocalMamba: Visual State Space Model with Windowed Selective Scan. 12-22 - Sifei Liu, Weili Nie, An-Chieh Cheng, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat:
Compositional Text-to-Image Generation with Feedforward Layout Generation. 23-33 - Haoran Xu, Ziqian Liu, Rong Fu, Zhongling Su, Zerui Wang, Zheng Cai, Zhilin Pei, Xingcheng Zhang:
PackMamba: Efficient Processing of Variable-Length Sequences in Mamba Training. 34-42 - Edwin Arkel Rios, Femiloye Oyerinde, Min-Chun Hu, Bo-Cheng Lai:
Down-Sampling Inter-layer Adapter for Parameter and Computation Efficient Ultra-Fine-Grained Image Recognition. 43-54 - Seyedarmin Azizi, Mahdi Nazemi, Massoud Pedram:
Memory-Efficient Vision Transformers: An Activation-Aware Mixed-Rank Compression Strategy. 55-66 - Anthony Sarah, Sharath Nittur Sridhar, Maciej Szankin, Sairam Sundaresan:
LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models. 67-74 - Nikhil Mehta, Jonathan Lorraine, Steve Masson, Ramanathan Arunachalam, Zaid Pervaiz Bhat, James Lucas, Arun George Zachariah:
Improving Hyperparameter Optimization with Checkpointed Model Weights. 75-96 - Gihwan Kim, Jemin Lee, Sihyeong Park, Yongin Kwon, Hyungshin Kim:
Mixed Non-linear Quantization for Vision Transformers. 97-112 - Federico Fontana, Romeo Lanzino, Anxhelo Diko, Gian Luca Foresti, Luigi Cinque:
CycleBNN: Cyclic Precision Training in Binary Neural Networks. 113-130 - Jiantao Wu, Shentong Mo, Sara Atito, Zhenhua Feng, Josef Kittler, Muhammad Awais:
DailyMAE: Towards Pretraining Masked Autoencoders in One Day. 131-149 - Ofir Gordon, Elad Cohen, Hai Victor Habi, Arnon Netzer:
EPTQ: Enhanced Post-training Quantization via Hessian-Guided Network-Wise Optimization. 150-166 - Sota Kato, Hinako Mitsuoka, Kazuhiro Hotta:
Generalized SAM: Efficient Fine-Tuning of SAM for Variable Input Image Sizes. 167-182 - Huan Wang, Feitong Tan, Ziqian Bai, Yinda Zhang, Shichen Liu, Qiangeng Xu, Menglei Chai, Anish Prabhu, Rohit Pandey, Sean Fanello, Zeng Huang, Yun Fu:
LightAvatar: Efficient Head Avatar as Dynamic Neural Light Field. 183-201 - Richa Upadhyay, Ronald Phlypo, Rajkumar Saini, Marcus Liwicki:
Giving Each Task what it Needs Leveraging Structured Sparsity for Tailored Multi-Task Learning. 202-218 - Xinyi Yu, Runan Yin, Zhihao Lin, Yongtao Wang:
ERF-NAS: Efficient Receptive Field-Based Zero-Shot NAS for Object Detection. 219-234 - Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato:
CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge. 235-251 - Maxime Girard, Victor Quétu, Samuel Tardieu, Van-Tam Nguyen, Enzo Tartaglione:
Memory-Optimized Once-For-All Network. 252-267 - Hui Shen, Zhongwei Wan, Xin Wang, Mi Zhang:
Famba-V: Fast Vision Mamba with Cross-Layer Token Fusion. 268-278 - Francesco Pasti, Marina Ceccon, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto, Nicola Bellotto:
Latent Distillation for Continual Object Detection at the Edge. 279-294 - Sudhakar Sah, Darshan C. Ganji, Matteo Grimaldi, Ravish Kumar, Alexander Hoffman, Honnesh Rohmetra, Ehsan Saboori:
MCUBench: A Benchmark of Tiny Object Detectors on MCUs. 295-311 - Federico Betti, Lorenzo Baraldi, Lorenzo Baraldi, Rita Cucchiara, Nicu Sebe:
Optimizing Resource Consumption in Diffusion Models Through Hallucination Early Detection. 312-326
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