Welcome to the space for the Computer Vision Reading Group, hosted by the Computer Vision Research Group at the Department of Computer Science, University of Sheffield!
Our group convenes to explore cutting-edge research, discuss pivotal papers, and delve into emerging trends in CV. Involved topics may include, but are not limited to, object detection, semantic segmentation, medical image analysis, generative AI, foundation models, and multimodal learning.
The events will normally take place every three weeks from 4 PM to 5 PM, on Wednesdays, at Ada Lovelace (108) meeting room.
The slides and recordings will be shared at internal Google Drive space.
We welcome students and academic staff from various groups and departments who share a genuine interest in advancing their understanding of this dynamic field, as well as those who are willing to help others advance their knowledge beyond their own progression. Please email me if you are willing to propose and deliver a presentation. You can do it either with or without a partner.
| Paper Title (link) | Presenter | Time / Place | Notes |
|---|---|---|---|
| TBD | Yanran Zhang | 26th June, 2024, 4pm-5pm / Ada Lovelace | |
| TBD | TBD | TBD |
| Paper Title (link) | Presenter | Time / Place | Notes |
|---|---|---|---|
| Wang, Z., Bovik, A.C., Sheikh, H.R. and Simoncelli, E.P., 2004. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing (link) Nilsson, J. and Akenine-Möller, T., 2020. Understanding SSIM. (link) Zhang, R., Isola, P., Efros, A.A., Shechtman, E. and Wang, O., 2018. The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. (link) |
Eleftherios Ioannou | 22nd May, 2024, 4pm-5pm / Ada Lovelace | Topic: Image Quality Assessment: Understanding SSIM (and LPIPS) Previously arranged on 15th May; Postponed to 22nd May. |
| Shi, Y., Wang, P., Ye, J., Long, M., Li, K. and Yang, X., 2023. Mvdream: Multi-view diffusion for 3d generation. arXiv preprint arXiv:2308.16512 (link) Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R. and Ng, R., 2021. Nerf: Representing scenes as neural radiance fields for view synthesis. Communications of the ACM, 65(1), pp.99-106 (link) Poole, B., Jain, A., Barron, J.T. and Mildenhall, B., 2022. Dreamfusion: Text-to-3d using 2d diffusion. arXiv preprint arXiv:2209.14988 (link) |
Ming He | 24th April, 2024, 4pm-5pm / Ada Lovelace | Topic: Using 2D Diffusion Model for 3D Content Generation |
| Chefer, Hila, et al. "Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models." ACM Transactions on Graphics (TOG) 42.4 (2023) (link) Feng, Weixi, et al. "Training-free structured diffusion guidance for compositional text-to-image synthesis." ICLR 2023 (link) Chen, Minghao, Iro Laina, and Andrea Vedaldi. "Training-free layout control with cross-attention guidance." Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2024. (link) |
Xiaoqi Zhuang | 10th April, 2024, 4pm-5pm / Ada Lovelace | Topic: Compositional Generation Challeng Previously arranged on 3rd April; Postponed to 10th April. |
| Rombach, Robin, et al. "High-resolution image synthesis with latent diffusion models." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2022. (link) Peebles, William, and Saining Xie. "Scalable diffusion models with transformers." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023. (link) |
Farheen Ramzan & Sijie Li | 13th March, 2024, 4pm-5pm / Ada Lovelace | Topic: Diffusion-based Generative Modeling Methods and Applications |