The workshop aims to explore the use of synthetic data in training and evaluating computer vision models, as well as in other related domains. During the last decade, advancements in computer vision were catalyzed by the release of painstakingly curated human-labeled datasets. Recently, people have increasingly resorted to synthetic data as an alternative to laborintensive human-labeled datasets for its scalability, customizability, and costeffectiveness. Synthetic data offers the potential to generate large volumes of diverse and high-quality vision data, tailored to specific scenarios and edge cases that are hard to capture in real-world data. However, challenges such as the domain gap between synthetic and real-world data, potential biases in synthetic generation, and ensuring the generalizability of models trained on synthetic data remain. We hope the workshop can provide a forum to discuss and encourage further exploration in these areas.
| DDOS: The Drone Depth and Obstacle Segmentation Dataset. Benedikt Kolbeinsson, Krystian Mikolajczyk |
| From NeRF to 3DGS: A Leap in Stereo Dataset Quality?. Magnus Kaufmann Gjerde, Filip Slezák, Joakim Bruslund Haurum, Thomas B. Moeslund |
| Training Robust Classifiers with Diffusion Denoised Examples. Chandramouli Shama Sastry, Sri Harsha Dumpala, Sageev Oore |
| Uncertainty Inclusive Contrastive Learning for Leveraging Synthetic Images. Fiona Cai, Emily Mu, John Guttag |
| HDL-SAM: A Hybrid Deep Learning Framework for High-Resolution Imaging in Scanning Acoustic Microscopy. Akshit Sharma, Ayush Somani, Pragyan Banerjee, Anowarul Habib |
| MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. Linyan Yang, Lukas Hoyer, Mark Weber, Tobias Fischer, Dengxin Dai, Laura Leal-Taixé, Daniel Cremers, Marc Pollefeys, Luc Van Gool |
| An Approach to Synthesize Thermal Infrared Ship Images. Doan Thinh Vo |
| LAESI: Leaf Area Estimation with Synthetic Imagery. Jacek Kałużny, Yannik Schreckenberger, Karol Cyganik, Peter Annighöfer, Soren Pirk, Dominik Michels, Mikolaj Cieslak, Farhah Assaad, Bedrich Benes, Wojtek Palubicki |
| GenAI-Bench: A Holistic Benchmark for Compositional Text-to-Visual Generation. Baiqi-Li, Zhiqiu Lin, Deepak Pathak, Jiayao Emily Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan |
| SEVD: Synthetic Event-based Vision Dataset for Ego and Fixed Traffic Perception. Manideep Reddy Aliminati, Bharatesh Chakravarthi, Aayush Atul Verma, Arpitsinh Vaghela, Hua Wei, Xuesong Zhou, Yezhou Yang |
| Implicit Neural Clustering. Thomas Kreutz, Max Mühlhäuser, Alejandro Sanchez Guinea |
| Training with Real instead of Synthetic Generated Images Still Performs Better. Scott Geng, Ranjay Krishna, Pang Wei Koh |
| A Neural Model for High-Performance Scanning Electron Microscopy Image Simulation of Porous Materials. Tim Dahmen |
| S2MGen: A Synthetic Skin Mask Generator for Improving Segmentation. Subhadra Gopalakrishnan, Trisha Mittal, Jaclyn Pytlarz, Yuheng Zhao |
| Self-Distillation on Conditional Spatial Activation Maps for ForeGround-BackGround Segmentation. Yeruru Asrar Ahmed, Anurag Mittal |
| GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning. Mehran Kazemi, Hamidreza Alvari, Ankit Anand, Jialin Wu, Xi Chen, Radu Soricut |
| CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion. Geonmo Gu, Sanghyuk Chun, Wonjae Kim, HeeJae Jun, Yoohoon Kang, Sangdoo Yun |
| Video2Game: Real-time, Interactive, Realistic and Browser-Compatible Environment from a Single Video. Hongchi Xia, Zhi-Hao Lin, Wei-Chiu Ma, Shenlong Wang |
| UrbanIR: Large-Scale Urban Scene Inverse Rendering from a Single Video. Zhi-Hao Lin, Bohan Liu, Yi-Ting Chen, David Forsyth, Jia-Bin Huang, Anand Bhattad, Shenlong Wang |
| Gen2Det: Generate to Detect. Saksham Suri, Fanyi Xiao, Animesh Sinha, Sean Culatana, Raghuraman Krishnamoorthi, Chenchen Zhu, Abhinav Shrivastava |
| DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Grading. Man M. Ho, Elham Ghelichkhan, Yosep Chong, Yufei Zhou, Beatrice S. Knudsen, Tolga Tasdizen |
| On the Equivalency, Substitutability, and Flexibility of Synthetic Data. Che-Jui Chang, Danrui Li, Seonghyeon Moon, Mubbasir Kapadia |
| Beyond Internet Images: Evaluating Vision-Language Models for Domain Generalization on Synthetic-to-Real Industrial Datasets. Louis Hémadou, Héléna Vorobieva, Ewa Kijak, Frederic Jurie |
| DiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection. Donggeun Ko, Sangwoo Jo, Dongjun Lee, Namjun Park, Jaekwang KIM |
| Balancing Quality and Quantity: The Impact of Synthetic Data on Smoke Detection Accuracy in Computer Vision. Ethan Seefried, Changsoo Jung, Jack Fitzgerald, Mariah Bradford, Trevor Chartier, Nathaniel Blanchard |
| Object-Conditioned Energy-Based Model for Attention Map Alignment in Text-to-Image Diffusion Models. Yasi Zhang, Peiyu Yu, Ying Nian Wu |
| DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control. Yuru Jia, Lukas Hoyer, Shengyu Huang, Tianfu Wang, Luc Van Gool, Konrad Schindler, Anton Obukhov |
| Diffusion Models for Open-Vocabulary Segmentation. Laurynas Karazija, Iro Laina, Andrea Vedaldi, Christian Rupprecht |
| CinePile: A Long Video Question Answering Dataset and Benchmark. Ruchit Rawal, Khalid Saifullah, Ronen Basri, David Jacobs, Gowthami Somepalli, Tom Goldstein |
| m&m's: A Benchmark to Evaluate Tool-Use for multi-step multi-modal Tasks. Zixian Ma, Weikai Huang, Jieyu Zhang, Tanmay Gupta, Ranjay Krishna |
| Harlequin: Color-driven Generation of Synthetic Data for Referring Expression Comprehension. Luca Parolari, Elena Izzo, Lamberto Ballan |
| Inclusive Portrait Lighting Estimation Model Leveraging Graphic-Based Synthetic Data. Kin Ching Lydia Chau, Tao LI, Ruowei Jiang, Zhi Yu, Panagiotis-Alexandros Bokaris |
| Attributed Synthetic Data Generation for Zero-shot Image Classification. Shijian Wang, Linxin Song, Ryotaro Shimizu, Masayuki Goto, Hanqian wu |
| A Benchmark Synthetic Dataset for C-SLAM in Service Environments. Harin Park, Inha Lee, Minje Kim, Hyungyu Park, Kyungdon Joo |
| Compositional Learning of Visually-Grounded Concepts Using Reinforcement. Zijun Lin, Haidi Azaman, M Ganesh Kumar, Cheston Tan |
| Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models. Yushi Hu, Otilia Stretcu, Chun-Ta Lu, Krishnamurthy Viswanathan, Kenji Hata, Enming Luo, Ranjay Krishna, Ariel Fuxman |
| DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback. Jiao Sun, Deqing Fu, Yushi Hu, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd van Steenkiste, Ranjay Krishna, Cyrus Rashtchian |
| SIFTer: Self-improving Synthetic Datasets for Pre-training Classification Models. Ryo Hayamizu, Shota Nakamura, Sora Takashima, Hirokatsu Kataoka, Ikuro Sato, Nakamasa Inoue, Rio Yokota |
| R3DS: Reality-linked 3D Scenes for Panoramic Scene Understanding. Qirui Wu, Sonia Raychaudhuri, Daniel Ritchie, Manolis Savva, Angel X Chang |
| Intrinsic LoRA: A Generalist Approach for Discovering Knowledge in Generative Models. Xiaodan Du, Nicholas Kolkin, Greg Shakhnarovich, Anand Bhattad |
| XIMAGENET-12: An Explainable Visual Benchmark Dataset for Model Robustness Evaluation. Qiang Li, Dan Zhang, Shengzhao Lei, Xun Zhao, WeiWei Li, Porawit Kamnoedboon, Junhao Dong, Shuyan Li |
| Paved2Paradise: Cost-Effective and Scalable LiDAR Simulation by Factoring the Real World. Michael A. Alcorn, Noah Schwartz |
| Virtually Enriched NYU Depth V2 Dataset for Monocular Depth Estimation: Do We Need Artificial Augmentation?. Dmitry Yu. Ignatov, Andrey Ignatov, Radu Timofte |
| SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?. Hasan Abed Al Kader Hammoud, Hani Itani, Fabio Pizzati, Adel Bibi, Bernard Ghanem |
Accepted papers will be allocated a poster presentation and displayed on
the workshop website. In addition, we will offer a Best Long Paper
award, Best Paper Runner-up award, and Best Short Paper with oral
presentation.
