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ORCID17th ECCV 2022: Tel Aviv, Israel - Volume 23
- Shai Avidan, Gabriel J. Brostow
, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner:
Computer Vision - ECCV 2022 - 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXIII. Lecture Notes in Computer Science 13683, Springer 2022, ISBN 978-3-031-20049-6 - Hengyuan Ma, Li Zhang, Xiatian Zhu, Jianfeng Feng:
Accelerating Score-Based Generative Models with Preconditioned Diffusion Sampling. 1-16 - Vlas Zyrianov, Xiyue Zhu, Shenlong Wang:
Learning to Generate Realistic LiDAR Point Clouds. 17-35 - Tuan-Anh Vu, Duc Thanh Nguyen, Binh-Son Hua, Quang-Hieu Pham, Sai-Kit Yeung:
RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds. 36-52 - Cairong Wang, Yiming Zhu, Chun Yuan:
Diverse Image Inpainting with Normalizing Flow. 53-69 - José Lezama, Huiwen Chang, Lu Jiang, Irfan Essa:
Improved Masked Image Generation with Token-Critic. 70-86 - Junghyuk Lee, Jong-Seok Lee:
TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation. 87-103 - Zikun Chen, Ruowei Jiang, Brendan Duke, Han Zhao, Parham Aarabi:
Exploring Gradient-Based Multi-directional Controls in GANs. 104-119 - Tianyu Wang, Miaomiao Liu, Kee Siong Ng:
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition. 120-135 - Hong-Wing Pang, Yingshu Chen, Phuoc-Hieu Le, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung:
Neural Scene Decoration from a Single Photograph. 136-152 - Kai Yao, Penglei Gao, Xi Yang, Jie Sun, Rui Zhang, Kaizhu Huang:
Outpainting by Queries. 153-169 - Sam Bond-Taylor, Peter Hessey, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks:
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes. 170-188 - Adéla Subrtová, David Futschik, Jan Cech, Michal Lukác, Eli Shechtman, Daniel Sýkora:
ChunkyGAN: Real Image Inversion via Segments. 189-204 - Omri Avrahami, Dani Lischinski, Ohad Fried:
GAN Cocktail: Mixing GANs Without Dataset Access. 205-221 - Mingfei Chen, Jianfeng Zhang, Xiangyu Xu, Lijuan Liu, Yujun Cai, Jiashi Feng, Shuicheng Yan:
Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering. 222-239 - Yichen Sheng, Yifan Liu, Jianming Zhang, Wei Yin, A. Cengiz Öztireli, He Zhang, Zhe Lin, Eli Shechtman, Bedrich Benes:
Controllable Shadow Generation Using Pixel Height Maps. 240-256 - Jovita Lukasik, Steffen Jung, Margret Keuper:
Learning Where to Look - Generative NAS is Surprisingly Efficient. 257-273 - Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi S. Jaakkola:
Subspace Diffusion Generative Models. 274-289 - Jiaheng Wei, Minghao Liu, Jiahao Luo, Andrew Zhu, James Davis, Yang Liu:
DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training. 290-317 - Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan:
MINER: Multiscale Implicit Neural Representation. 318-333 - Hongwei Yong, Lei Zhang:
An Embedded Feature Whitening Approach to Deep Neural Network Optimization. 334-351 - Alp Yurtsever, Tolga Birdal, Vladislav Golyanik:
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization. 352-369 - Chang Liu, Shaofeng Zhang, Xiaokang Yang, Junchi Yan:
Self-supervised Learning of Visual Graph Matching. 370-388 - Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Chen, Ahmed Awadallah, Zhangyang Wang:
Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models. 389-405 - Gang-Xuan Lin, Shih-Wei Hu, Chun-Shien Lu:
QISTA-ImageNet: A Deep Compressive Image Sensing Framework Solving ℓ q-Norm Optimization Problem. 406-422 - Qiankun Gao, Chen Zhao, Bernard Ghanem, Jian Zhang:
R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning. 423-439 - Junbum Cha, Kyungjae Lee, Sungrae Park, Sanghyuk Chun:
Domain Generalization by Mutual-Information Regularization with Pre-trained Models. 440-457 - Damien Teney, Maxime Peyrard, Ehsan Abbasnejad:
Predicting Is Not Understanding: Recognizing and Addressing Underspecification in Machine Learning. 458-476 - Yunhao Ge, Harkirat S. Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet:
Neural-Sim: Learning to Generate Training Data with NeRF. 477-493 - Hanwei Fan, Jiandong Mu, Wei Zhang:
Bayesian Optimization with Clustering and Rollback for CNN Auto Pruning. 494-511 - Markus Hofinger, Erich Kobler, Alexander Effland, Thomas Pock:
Learned Variational Video Color Propagation. 512-530 - Fei Ye, Adrian G. Bors:
Continual Variational Autoencoder Learning via Online Cooperative Memorization. 531-549 - Yuanhao Xiong, Cho-Jui Hsieh:
Learning to Learn with Smooth Regularization. 550-565 - Rakib Hyder, Ken Shao, Boyu Hou, Panos P. Markopoulos, Ashley Prater-Bennette, M. Salman Asif:
Incremental Task Learning with Incremental Rank Updates. 566-582 - Yue Song, Nicu Sebe, Wei Wang:
Batch-Efficient EigenDecomposition for Small and Medium Matrices. 583-599 - Chengshuai Yang, Shiyu Zhang, Xin Yuan:
Ensemble Learning Priors Driven Deep Unfolding for Scalable Video Snapshot Compressive Imaging. 600-618 - Dongsheng An, Na Lei, Xianfeng Gu:
Approximate Discrete Optimal Transport Plan with Auxiliary Measure Method. 619-635 - Stefan Haller, Lorenz Feineis, Lisa Hutschenreiter, Florian Bernard, Carsten Rother, Dagmar Kainmüller, Paul Swoboda, Bogdan Savchynskyy:
A Comparative Study of Graph Matching Algorithms in Computer Vision. 636-653 - Debora Caldarola, Barbara Caputo, Marco Ciccone:
Improving Generalization in Federated Learning by Seeking Flat Minima. 654-672 - Liangzu Peng, Mahyar Fazlyab, René Vidal:
Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or Not. 673-691 - Matteo Boschini, Lorenzo Bonicelli, Angelo Porrello, Giovanni Bellitto, Matteo Pennisi, Simone Palazzo, Concetto Spampinato, Simone Calderara:
Transfer Without Forgetting. 692-709 - Farshid Varno, Marzie Saghayi, Laya Rafiee Sevyeri, Sharut Gupta, Stan Matwin, Mohammad Havaei:
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation. 710-726 - Xiao Gu, Yao Guo, Zeju Li, Jianing Qiu, Qi Dou, Yuxuan Liu, Benny Lo, Guang-Zhong Yang:
Tackling Long-Tailed Category Distribution Under Domain Shifts. 727-743 - Li Gao, Dong Nie, Bo Li, Xiaofeng Ren:
Doubly-Fused ViT: Fuse Information from Vision Transformer Doubly with Local Representation. 744-761
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