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ORCID19th ICCV Workshops 2023: Paris, France
- IEEE/CVF International Conference on Computer Vision, ICCV 2023 - Workshops, Paris, France, October 2-6, 2023. IEEE 2023, ISBN 979-8-3503-0744-3
- David Gillsjö
, Gabrielle Flood, Kalle Åström:
Polygon Detection for Room Layout Estimation using Heterogeneous Graphs and Wireframes. 1-10 - Maëlic Neau, Paulo E. Santos, Anne-Gwenn Bosser, Cédric Buche:
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph Generation. 11-20 - Dao Thauvin, Stéphane Herbin:
Knowledge Informed Sequential Scene Graph Verification Using VQA. 21-31 - Amit Aflalo, Shai Bagon, Tamar Kashti, Yonina C. Eldar:
DeepCut: Unsupervised Segmentation using Graph Neural Networks Clustering. 32-41 - Leon Mlodzian, Zhigang Sun, Hendrik Berkemeyer, Sebastian Monka, Zixu Wang, Stefan Dietze, Lavdim Halilaj, Juergen Luettin:
nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction. 42-52 - Osman Ülger, Yu Wang, Ysbrand Galama, Sezer Karaoglu, Theo Gevers, Martin R. Oswald:
Relational Prior Knowledge Graphs for Detection and Instance Segmentation. 53-61 - Julian Lorenz, Florian Barthel, Daniel Kienzle, Rainer Lienhart:
Haystack: A Panoptic Scene Graph Dataset to Evaluate Rare Predicate Classes. 62-70 - Rémy Sun, Diane Lingrand, Frédéric Precioso:
Exploring the Road Graph in Trajectory Forecasting for Autonomous Driving. 71-80 - Felix Holm, Ghazal Ghazaei, Tobias Czempiel, Ege Özsoy, Stefan Saur, Nassir Navab:
Dynamic Scene Graph Representation for Surgical Video. 81-87 - Azade Farshad, Yousef Yeganeh, Yu Chi, Chengzhi Shen, Björn Ommer, Nassir Navab:
SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis. 88-98 - Dario Garcia-Gasulla, Victor Gimenez-Abalos, Pablo A. Martin-Torres:
Padding Aware Neurons. 99-108 - Radu A. Cosma, Lukas Knobel, Putri A. van der Linden, David M. Knigge, Erik J. Bekkers:
Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks. 109-118 - Tom Edixhoven, Attila Lengyel, Jan C. van Gemert:
Using and Abusing Equivariance. 119-128 - Shunxin Wang, Christoph Brune, Raymond N. J. Veldhuis, Nicola Strisciuglio:
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning. 129-138 - Lorenzo Brigato, Stavroula G. Mougiakakou:
No Data Augmentation? Alternative Regularizations for Effective Training on Small Datasets. 139-148 - Rangel Daroya, Aaron Sun, Subhransu Maji:
COSE: A Consistency-Sensitivity Metric for Saliency on Image Classification. 149-158 - Ombretta Strafforello, Xin Liu, Klamer Schutte, Jan van Gemert:
Video BagNet: short temporal receptive fields increase robustness in long-term action recognition. 159-166 - Oindrila Saha, Subhransu Maji:
PARTICLE: Part Discovery and Contrastive Learning for Fine-grained Recognition. 167-176 - Thalles Silva, Hélio Pedrini, Adín Ramírez Rivera:
Self-supervised Learning of Contextualized Local Visual Embeddings. 177-186 - Alokendu Mazumder, Tirthajit Baruah, Akash Kumar Singh, Pagadala Krishna Murthy, Vishwajeet Pattanaik, Punit Rathore:
DeepVAT: A Self-Supervised Technique for Cluster Assessment in Image Datasets. 187-195 - Vassilis C. Nicodemou, Iason Oikonomidis, Antonis A. Argyros:
RV-VAE: Integrating Random Variable Algebra into Variational Autoencoders. 196-205 - Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers:
Geometric Contrastive Learning. 206-215 - Imanol González Estepa, Jesús M. Rodríguez-de-Vera, Bhalaji Nagarajan, Petia Radeva:
Good Fences Make Good Neighbours. 216-226 - Pranjay Shyam, Hyunjin Yoo:
Data Efficient Single Image Dehazing via Adversarial Auto-Augmentation and extended Atmospheric Scattering Model. 227-237 - Ahmed Radwan, Mohamed S. Shehata:
Distilling Part-whole Hierarchical Knowledge from a Huge Pretrained Class Agnostic Segmentation Framework. 238-246 - Vaibhav Ganatra:
Logarithm-transform aided Gaussian Sampling for Few-Shot Learning. 247-252 - Kowshik Thopalli, Devi S, Jayaraman J. Thiagarajan:
InterAug: A Tuning-Free Augmentation Policy for Data-Efficient and Robust Object Detection. 253-261 - Mayug Maniparambil, Chris Vorster, Derek Molloy, Noel Murphy, Kevin McGuinness, Noel E. O'Connor:
Enhancing CLIP with GPT-4: Harnessing Visual Descriptions as Prompts. 262-271 - Junting Pan, Ziyi Lin, Yuying Ge, Xiatian Zhu, Renrui Zhang, Yi Wang, Yu Qiao, Hongsheng Li:
Retrieving-to-Answer: Zero-Shot Video Question Answering with Frozen Large Language Models. 272-283 - Wei-Jhe Huang, Jheng-Hsien Yeh, Min-Hung Chen, Gueter Josmy Faure, Shang-Hong Lai:
Interaction-Aware Prompting for Zero-Shot Spatio-Temporal Action Detection. 284-293 - Zhihang Zhong, Mingxi Cheng, Zhirong Wu, Yuhui Yuan, Yinqiang Zheng, Ji Li, Han Hu, Stephen Lin, Yoichi Sato, Imari Sato:
ClipCrop: Conditioned Cropping Driven by Vision-Language Model. 294-304 - Reza Pourreza, Apratim Bhattacharyya, Sunny Panchal, Mingu Lee, Pulkit Madan, Roland Memisevic:
Painter: Teaching Auto-regressive Language Models to Draw Sketches. 305-314 - Bo Wang, Kaili Zhao, Hongyang Zhao, Shi Pu, Bo Xiao, Jun Guo:
Video Attribute Prototype Network: A New Perspective for Zero-Shot Video Classification. 315-324 - Anne Zonneveld, Albert Gatt, Iacer Calixto:
Video-and-Language (VidL) models and their cognitive relevance. 325-338 - Emmanuelle Salin, Stéphane Ayache, Benoît Favre:
Towards an Exhaustive Evaluation of Vision-Language Foundation Models. 339-352 - Sai Vidyaranya Nuthalapati, Anirudh Tunga:
Coarse to Fine Frame Selection for Online Open-ended Video Question Answering. 353-361 - Felix Rosberg, Eren Erdal Aksoy, Cristofer Englund, Fernando Alonso-Fernandez:
FIVA: Facial Image and Video Anonymization and Anonymization Defense. 362-371 - Sahar Husseini, Jean-Luc Dugelay:
A Comprehensive Framework for Evaluating Deepfake Generators: Dataset, Metrics Performance, and Comparative Analysis. 372-381 - David C. Epstein, Ishan Jain, Oliver Wang, Richard Zhang:
Online Detection of AI-Generated Images. 382-392 - Nicolas Beuve, Wassim Hamidouche, Olivier Déforges:
WaterLo: Protect Images from Deepfakes Using Localized Semi-Fragile Watermark. 393-402 - Soumyaroop Nandi, Prem Natarajan, Wael Abd-Almageed:
TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization. 403-414 - Sanjay Saha, Rashindrie Perera, Sachith Seneviratne, Tamasha Malepathirana, Sanka Rasnayaka, Deshani Geethika, Terence Sim, Saman K. Halgamuge:
Undercover Deepfakes: Detecting Fake Segments in Videos. 415-425 - Sarthak Kamat, Shruti Agarwal, Trevor Darrell, Anna Rohrbach:
Revisiting Generalizability in Deepfake Detection: Improving Metrics and Stabilizing Transfer. 426-435 - Sowmen Das, Md. Ruhul Amin:
Learning Interpretable Forensic Representations via Local Window Modulation. 436-447 - Peter Lorenz, Ricard L. Durall, Janis Keuper:
Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality. 448-459 - Assia Hamadene, Abdeldjalil Ouahabi, Abdenour Hadid:
Deepfakes Signatures Detection in the Handcrafted Features Space. 460-466 - Agil Aghasanli, Dmitry Kangin, Plamen Angelov:
Interpretable-through-prototypes deepfake detection for diffusion models. 467-474 - Pranav Balaji, Abhijit Das, Srijan Das, Antitza Dantcheva:
Attending Generalizability in Course of Deep Fake Detection by Exploring Multi-task Learning. 475-484 - Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen:
Improving Deep Learning on Hyperspectral Images of Grain by Incorporating Domain Knowledge from Chemometrics. 485-494 - Laurent Lejeune, Morgane Roussin, Bruno Leggio, Aurélia Vernay:
An Interpretable Framework to Characterize Compound Treatments on Filamentous Fungi using Cell Painting and Deep Metric Learning. 495-504 - Yuemin Wang, Thuan Ha, Kathryn Aldridge, Hema Sudhakar Duddu, Steve Shirtliffe, Ian Stavness:
Weed Mapping with Convolutional Neural Networks on High Resolution Whole-Field Images. 505-514 - Cees Jol, Junhan Wen, Jan van Gemert:
Non-Destructive Infield Quality Estimation of Strawberries using Deep Architectures. 515-524 - Ángela Casado-García, Jónathan Heras, Xabier Simon Martínez-Goñi, Jon Miranda-Apodaca, Usue Pérez-López:
Estimation of Crop Production by Fusing Images and Crop Features. 525-530 - Hao Song, Karim Panjvani, Zhigang Liu, Huzaifa Amar, Leon Kochian, Shengjian Ye, Xuan Yang, J. Allan Feurtado, Krunal Chavda, Karina Angela Chimbo Huatatoca, Mark G. Eramian:
Plant Root Occlusion Inpainting with Generative Adversarial Network. 531-539 - Nico Samà, Etienne David, Simone Rossetti, Alessandro Antona, Benjamin Franchetti, Fiora Pirri:
A new large dataset and a transfer learning methodology for plant phenotyping in Vertical Farms. 540-551 - Astrid Tempelaere, Leen Van Doorselaer, Jiaqi He, Pieter Verboven, Tinne Tuytelaars, Bart M. Nicolaï:
Deep Learning for Apple Fruit Quality Inspection using X-Ray Imaging. 552-560 - Vsevolod Cherepashkin, Erenus Yildiz, Andreas Fischbach, Leif Kobbelt, Hanno Scharr:
Deep learning based 3d reconstruction for phenotyping of wheat seeds: a dataset, challenge, and baseline method. 561-571 - Niklas Penzel, Jana Kierdorf, Ribana Roscher, Joachim Denzler:
Analyzing the Behavior of Cauliflower Harvest-Readiness Models by Investigating Feature Relevances. 572-581 - Ekin Celikkan, Mohammadmehdi Saberioon, Martin Herold, Nadja Klein:
Semantic Segmentation of Crops and Weeds with Probabilistic Modeling and Uncertainty Quantification. 582-592 - Mathieu Pagé Fortin:
Class-Incremental Learning of Plant and Disease Detection: Growing Branches with Knowledge Distillation. 593-603 - Feng Chen, Mario Valerio Giuffrida, Sotirios A. Tsaftaris:
Adapting Vision Foundation Models for Plant Phenotyping. 604-613 - Paul Melki, Lionel Bombrun, Boubacar Diallo, Jérôme Dias, Jean-Pierre Da Costa:
Group-Conditional Conformal Prediction via Quantile Regression Calibration for Crop and Weed Classification. 614-623 - Nikolaus Wagner, Grzegorz Cielniak:
Vision-based Monitoring of the Short-term Dynamic Behaviour of Plants for Automated Phenotyping. 624-633 - Dan Jeric Arcega Rustia, Guido Alexander Jansen, Selwin Hageraats, Joseph Peller, Rick van de Zedde, Cécile Marchennay, Wim Sangster, Gosia Blokker:
Rapid tomato DUS trait analysis using an optimized mobile-based coarse-to-fine instance segmentation algorithm. 634-642 - Frederic Tausch, Jan Wagner, Simon Klaus:
Pollinators as Data Collectors: Estimating Floral Diversity with Bees and Computer Vision. 643-650 - Mohamed M. Farag, Jana Kierdorf, Ribana Roscher:
Inductive Conformal Prediction for Harvest-Readiness Classification of Cauliflower Plants: A Comparative Study of Uncertainty Quantification Methods. 651-659 - Keyhan Najafian, Lingling Jin, H. Randy Kutcher, Mackenzie Hladun, Samuel Horovatin, Maria Alejandra Oviedo-Ludena, Sheila Maria Pereira De Andrade, Lipu Wang, Ian Stavness:
Detection of Fusarium Damaged Kernels in Wheat Using Deep Semi-Supervised Learning on a Novel WheatSeedBelt Dataset. 660-669 - Mohammed El Amine Sehaba, Carlos Fernando Crispim Junior, Laure Tougne Rodet:
Embedded plant recognition: a benchmark for low footprint deep neural networks. 670-677 - Zane K. J. Hartley, Rob J. Lind, Nicholas Smith, Bob Collison, Andrew P. French:
Unlocking Comparative Plant Scoring with Siamese Neural Networks and Pairwise Pseudo Labelling. 678-684 - Matthias Körschens, Solveig Franziska Bucher, Christine Römermann, Joachim Denzler:
Unified Automatic Plant Cover and Phenology Prediction. 685-693 - Antonio Pico Villalpando, Matthias Kubisch, David Colliaux, Peter Hanappe, Verena V. Hafner:
Reinforcement learning with space carving for plant scanning. 694-701 - Moritz Schauer, Renke Hohl, Dennis Vaupel, Diethelm Bienhaus, Seyed Eghbal Ghobadi:
Towards Automated Regulation of Jacobaea Vulgaris in Grassland using Deep Neural Networks. 702-711 - Theophile Gentilhomme, Michael Villamizar, Jerome Corre, Jean-Marc Odobez:
Efficient Grapevine Structure Estimation in Vineyards Conditions. 712-720 - Youcef Djenouri, Ahmed Nabil Belbachir:
A Hybrid Visual Transformer for Efficient Deep Human Activity Recognition. 721-730 - Xijun Wang, Xiaojie Chu, Chunrui Han, Xiangyu Zhang:
SCSC: Spatial Cross-scale Convolution Module to Strengthen both CNNs and Transformers. 731-741 - Chandra Sekhar Vorugunti, Avinash Gautam, Viswanath Pulabaigari, Sreeja SR, Rama Krishna Sai G:
TSOSVNet: Teacher-student collaborative knowledge distillation for Online Signature Verification. 742-751 - Jitesh Jain, Anukriti Singh, Nikita Orlov, Zilong Huang, Jiachen Li, Steven Walton, Humphrey Shi:
SeMask: Semantically Masked Transformers for Semantic Segmentation. 752-761 - Kun Li, George Vosselman, Michael Ying Yang:
Interactive Image Segmentation with Cross-Modality Vision Transformers. 762-772 - Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund:
Which Tokens to Use? Investigating Token Reduction in Vision Transformers. 773-783 - Anindya Mondal, Sauradip Nag, Joaquin M. Prada, Xiatian Zhu, Anjan Dutta:
Actor-agnostic Multi-label Action Recognition with Multi-modal Query. 784-794 - Jun-Sang Yoo, Hongjae Lee, Seung-Won Jung:
Hierarchical Spatiotemporal Transformers for Video Object Segmentation. 795-805 - Alexandre Englebert, Sédrick Stassin, Géraldin Nanfack, Sidi Ahmed Mahmoudi, Xavier Siebert, Olivier Cornu, Christophe De Vleeschouwer:
Explaining through Transformer Input Sampling. 806-815 - Partha Das, Maxime Gevers, Sezer Karaoglu, Theo Gevers:
IDTransformer: Transformer for Intrinsic Image Decomposition. 816-825 - Weixuan Sun, Yanhao Zhang, Zhen Qin, Zheyuan Liu, Lin Cheng, Fanyi Wang, Yiran Zhong, Nick Barnes:
All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation. 826-837 - Jakob Drachmann Havtorn, Amélie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi:
MSViT: Dynamic Mixed-scale Tokenization for Vision Transformers. 838-848 - Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger:
TransInpaint: Transformer-based Image Inpainting with Context Adaptation. 849-858 - Ali Diba, Vivek Sharma, Mohammad Mahdi Arzani, Luc Van Gool:
Spatio-Temporal Convolution-Attention Video Network. 859-869 - Ziyang Wang, Congying Ma:
Dual-Contrastive Dual-Consistency Dual-Transformer: A Semi-Supervised Approach to Medical Image Segmentation. 870-879 - Christian Homeyer, Christoph Schnörr:
On Moving Object Segmentation from Monocular Video with Transformers. 880-891 - Prajwal Ganugula, Y. S. S. S. Santosh Kumar, N. K. Sagar Reddy, Prabhath Chellingi, Avinash Thakur, Neeraj Kasera, C. Shyam Anand:
MOSAIC: Multi-Object Segmented Arbitrary Stylization Using CLIP. 892-903 - Felix Hertlein, Alexander Naumann:
Template-guided Illumination Correction for Document Images with Imperfect Geometric Reconstruction. 904-913 - Renaud Vandeghen, Gilles Louppe, Marc Van Droogenbroeck:
Adaptive Self-Training for Object Detection. 914-923 - Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael J. Jones:
Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. 924-932 - Aleksandar Shtedritski, Andrea Vedaldi, Christian Rupprecht:
Learning Universal Semantic Correspondences with No Supervision and Automatic Data Curation. 933-943 - Shijie Li, Rong Li, Juergen Gall:
Semantic RGB-D Image Synthesis. 944-952 - Lucian Bicsi, Bogdan Alexe, Radu Tudor Ionescu, Marius Leordeanu:
JEDI: Joint Expert Distillation in a Semi-Supervised Multi-Dataset Student-Teacher Scenario for Video Action Recognition. 953-962 - Ci-Siang Lin, Min-Hung Chen, Yu-Chiang Frank Wang:
Frequency-Aware Self-Supervised Long-Tailed Learning. 963-972 - Youssef Dawoud, Gustavo Carneiro, Vasileios Belagiannis:
SelectNAdapt: Support Set Selection for Few-Shot Domain Adaptation. 973-982 - Alina Marcu, Mihai Cristian Pîrvu, Dragos Costea, Emanuela Haller, Emil Slusanschi, Nabil Belbachir, Rahul Sukthankar, Marius Leordeanu:
Self-supervised Hypergraphs for Learning Multiple World Interpretations. 983-992 - Tianpeng Bao, Jiadong Chen, Wei Li, Xiang Wang, Jingjing Fei, Liwei Wu, Rui Zhao, Ye Zheng:
MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection. 993-1002 - Hoàng-Ân Lê, Minh-Tan Pham:
Self-training and multi-task learning for limited data: evaluation study on object detection. 1003-1009 - Minho Park, Hyung-Il Kim, Hwa Jeon Song, Dong-oh Kang:
Augmenting Features via Contrastive Learning-based Generative Model for Long-Tailed Classification. 1010-1019 - Khanh-Binh Nguyen, Joon-Sung Yang:
Boosting Semi-Supervised Learning by bridging high and low-confidence predictions. 1020-1030 - Athanasios Psaltis, Anestis Kastellos, Charalampos Z. Patrikakis, Petros Daras:
FedLID: Self-Supervised Federated Learning for Leveraging Limited Image Data. 1031-1040 - Jose Sosa, David C. Hogg:
A Horse with no Labels: Self-Supervised Horse Pose Estimation from Unlabelled Images and Synthetic Prior. 1041-1048 - Chunsan Hong, Byunghee Cha, Bohyung Kim, Tae-Hyun Oh:
Enhancing Classification Accuracy on Limited Data via Unconditional GAN. 1049-1057 - Kamil Kwarciak, Marek Wodzinski:
Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects. 1058-1066 - Laurenz Reichardt, Nikolas Ebert, Oliver Wasenmüller:
360° from a Single Camera: A Few-Shot Approach for LiDAR Segmentation. 1067-1075 - Patrick Takenaka, Johannes Maucher, Marco F. Huber:
Guiding Video Prediction with Explicit Procedural Knowledge. 1076-1084 - John R. Kender, Parijat Dube, Zhengyang Han, Bishwaranjan Bhattacharjee:
G2L: A High-Dimensional Geometric Approach for Automatic Generation of Highly Accurate Pseudo-labels. 1085-1094 - Sangbeom Lim, Seungryong Kim:
Image Guided Inpainting with Parameter Efficient Learning. 1095-1103 - Jiali Zheng, Youngkyoon Jang, Athanasios Papaioannou, Christos Kampouris, Rolandos Alexandros Potamias, Foivos Paraperas Papantoniou, Efstathios Galanakis, Ales Leonardis, Stefanos Zafeiriou:
ILSH: The Imperial Light-Stage Head Dataset for Human Head View Synthesis. 1104-1112 - Youngkyoon Jang, Jiali Zheng, Jifei Song, Helisa Dhamo, Eduardo Pérez-Pellitero, Thomas Tanay, Matteo Maggioni, Richard Shaw, Sibi Catley-Chandar, Yiren Zhou, Jiankang Deng, Ruijie Zhu, Jiahao Chang, Ziyang Song, Jiahuan Yu, Tianzhu Zhang, Khanh-Binh Nguyen, Joon-Sung Yang, Andreea Dogaru, Bernhard Egger, Heng Yu, Aarush Gupta, Joel Julin, László A. Jeni, Hyeseong Kim, Jungbin Cho, Dosik Hwang, Deukhee Lee, Doyeon Kim, Dongseong Seo, SeungJin Jeon, YoungDon Choi, Jun Seok Kang, Ahmet Cagatay Seker, Sang Chul Ahn, Ales Leonardis, Stefanos Zafeiriou:
VSCHH 2023: A Benchmark for the View Synthesis Challenge of Human Heads. 1113-1120 - Ziwei Liu, Yongtao Wang, Xiaojie Chu, Nan Dong, Shengxiang Qi, Haibin Ling:
A Simple and Generic Framework for Feature Distillation via Channel-wise Transformation. 1121-1130 - Furkan Kinli, Doga Yilmaz, Baris Özcan, Furkan Kiraç:
Deterministic Neural Illumination Mapping for Efficient Auto-White Balance Correction. 1131-1139 - Tom Pégeot, Inna Kucher, Adrian Popescu, Bertrand Delezoide:
A Comprehensive Study of Transfer Learning under Constraints. 1140-1149 - Tomás Berriel Martins, Javier Civera:
Ray-Patch: An Efficient Querying for Light Field Transformers. 1150-1155 - Tomaso Trinci, Tommaso Bianconcini, Leonardo Sarti, Leonardo Taccari, Francesco Sambo:
Cross-model temporal cooperation via saliency maps for efficient frame classification. 1156-1160 - Ivan Lazarevich, Matteo Grimaldi, Ravish Kumar, Saptarshi Mitra, Shahrukh Khan, Sudhakar Sah:
YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems. 1161-1170