Our Projects


There are many ongoing and supported research projects in the VIMS lab. Currently, work is being done in the following research areas:
Stereo Vision, Machine Learning, Image Processing, Virtual Reality, Data Mining, Biomedical Image Analysis, and more.

Publications


2024


Conference Papers

  • Bhattarai A, Jin J and Kambhamettu C. Detachable Encoder Transformer for SCR Detection. IOVS 2024:ARVO E-Abstract
  • Seyedalireza Khoshsirat and Chandra Kambhamettu. "Improving Normalization with the James-Stein Estimator", IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.
  • Sheshappanavar, Shivanand, Tejas Anvekar, Shivanand Kundargi, Yufan Wang, and Chandra Kambhamettu, "A Benchmark Grocery Dataset of Realworld Point Clouds from Single View." In 2024 International Conference on 3D Vision (3DV), IEEE, 2024.

2023


Competitions

  • Seyedalireza Khoshsirat from the VIMS Lab is First on the VizWiz-VQA-Grounding Challenge 2023 leaderboard. Link to the leaderboard.

Journal Papers

  • Seyedalireza Khoshsirat and Chandra Kambhamettu. "A transformer-based neural ODE for dense prediction", Machine Vision and Applications, 2023. Link to the paper.
  • Okorie, A., Kambhamettu, C. & Makrogiannnis, S. Unsupervised learning of probabilistic subspaces for multi-spectral and multi-temporal image-based disaster mapping. Machine Vision and Applications 34, 103 (2023). Link to the paper.

Conference Papers

  • Huining Liang and Chandra Kambhamettu. "Edge-guided Image Inpainting with Transformer", International Symposium on Visual Computing (ISVC), October 2023.
  • Rohit Venkata Sai Dulam and Chandra Kambhamettu. "SODAWideNet - Salient Object Detection with an Attention augmented Wide Encoder Decoder network without ImageNet pre-training", International Symposium on Visual Computing (ISVC), October 2023.
  • Yi Liu, Su Peng, Jeffrey Caplan, and Chandra Kambhamettu, "Pick and Trace: Instance Segmentation for Filamentous Objects with a Recurrent Neural Network", 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). October 8-12, 2023, Vancouver.
  • Seyedalireza Khoshsirat and Chandra Kambhamettu. "Sentence Attention Blocks for Answer Grounding", Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • Seyedalireza Khoshsirat and Chandra Kambhamettu. "Empowering Visually Impaired Individuals: A Novel Use of Apple Live Photos and Android Motion Photos", 25th Irish Machine Vision and Image Processing Conference, 2023.
  • Seyedalireza Khoshsirat and Chandra Kambhamettu. "Embedding Attention Blocks for the VizWiz Answer Grounding Challenge", VizWiz Grand Challenge Workshop, 2023.
  • Chandra Kambhamettu, "3DSAINT Representation for 3D Point Clouds", Workshop on Computer Vision for Mixed Reality (CVPRW-CV4MR), 2023.
  • Shivanand Venkanna Sheshappanavar, and Chandra Kambhamettu. "Local Neighborhood Features for 3D Classification", 22nd Scandinavian Conference In Image Analysis (SCIA), Levi (Lapland), Finland, Springer International Publishing, April 2023.
  • Rohit Venkata Sai Dulam, Emily Fedders, Andrew Mahoney, and Chandra Kambhamettu. "ConvSegFormer - A convolution aided SegFormer architecture for detection of discontinuities in wrapped interferometric phase imagery of Sea Ice", 22nd Scandinavian Conference In Image Analysis (SCIA), Levi (Lapland), Finland, Springer International Publishing, April 2023.

2022


Competitions

  • Seyedalireza Khoshsirat from the VIMS Lab is First on the VizWiz-VQA-Grounding Challenge 2022 leaderboard. Link to the leaderboard.
  • Shivanand Venkanna Sheshappanavar from the VIMS Lab is among the top 10 on the real-world objects benchmark ScanObjectNN dataset leaderboard. Link to the leaderboard.

Conference Papers

  • Vinit Veerendraveer Singh and Chandra Kambhamettu. "Classification of Biomedical Journal Images using Retargeting-Based Data Augmentation and Visually Explainable Attention Priors" (BMVC), 2022.
  • Michael Pergeorelis, Maxim Bazik, Philip Saponaro, Joong Kim, and Chandra Kambhamettu. "Synthetic Data for Semantic Segmentation in Underwater Imagery", Global Oceans 2022: Hampton Roads, October 2022.
  • Seyedalireza Khoshsirat and Chandra Kambhamettu. "Semantic Segmentation using Neural Ordinary Differential Equations", International Symposium on Visual Computing (ISVC), October 2022.
  • Ashuta Bhattarai, Chandra Kambhamettu, and Jing Jin. "CUNet: Towards continuous multi-class contour detection for retinal layer segmentation in OCT images", 29th IEEE International Conference on Image Processing (IEEE ICIP), October 2022.
  • Rohit Venkata Sai Dulam, Kelsey Kaplan, and Chandra Kambhamettu. "Deep Learning-based Sea Ice Lead Detection from WorldView and Sentinel SAR Imagery", IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS), August 2022.
  • Kelsey Kaplan and Chandra Kambhamettu. "A Novel Methodology for High-Resolution Sea Ice Motion Estimation", IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS), August 2022.
  • Shivanand Venkanna Sheshappanavar, and Chandra Kambhamettu. "SimpleView++: Neighborhood Views for Point Cloud Classification", Proceedings of the IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), August 2022.
  • Yi Liu, Jeffrey Caplan, Chandra Kambhamettu, "Extraction and Quantification of Actin Cytoskeleton in Microscopic Images Using a Deep Learning Based Framework and a Curve Clustering Model", 26th International Conference on Pattern Recognition (ICPR), 2022
  • Singh, Vinit Veerendraveer and Chandra Kambhamettu. "AIM: an Auto-Augmenter for Images and Meshes". 2022 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  • Jin J, Bhattarai A, Miller R, Kolb EA and Kambhamettu C. A deep learning system for sickle cell retinopathy detection using retinal OCT images from children with sickle cell disease. IOVS 2022:ARVO E-Abstract

2021


Conference Papers

  • Singh, Vinit Veerendraveer, Venkanna Sheshappanavar, Shivanand, and Chandra Kambhamettu. "MeshNet++: A Network with a Face". Proceedings of the 29th ACM International Conference on Multimedia. 2021., 1-9 (Oral)
  • Venkanna Sheshappanavar, Shivanand, Singh, Vinit Veerendraveer, and Chandra Kambhamettu. "PatchAugment: Local Neighborhood Augmentation in Point Cloud Classification" Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops. 2021.
  • Olson, Lauren, Chandra Kambhamettu, and Kathleen McCoy. "Towards Using Live Photos to Mitigate Image Quality Issues In VQA Photography." The 23rd International ACM SIGACCESS Conference on Computers and Accessibility. 2021.

Displaying 30/275 publications. Full Listing Here

Our Team


The VIMS Lab is home to Postdocs, Doctoral Students, and Masters Students who participate in a wide variety of
research topics relating to Computer Vision, Machine Learning, Deep Learning, and Image Processing.

Hi, I am Dr. Chandra Kambhamettu! I am the Director & Research Advisor of VIMS Lab.

Dr. Chandra Kambhamettu

Director & Research Advisor

Hi, I am Dr. Philip Saponaro! I am a Associate Scientist at the VIMS Lab. My research interests lie in Multimodal Stereo Vision, Augmented and Virtual Reality, and Machine Learning.

Dr. Philip Saponaro

Associate Scientist

Hi, I am Ali Khoshsirat! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning, Semantic Segmentation, Convolutional Networks, and Machine Learning.
Personal Website

Ali Khoshsirat

Ph.D. Student

Hi, I am Ashuta Bhattarai! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep learning, Image Classification, Virtual Reality, and Machine Learning.
Contact Email

Ashuta Bhattarai

Ph.D. Student

Hi, I am Rohit Venkata Sai Dulam! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning and Programmable Intuition.
Contact Email

Rohit Venkata Sai Dulam

Ph.D. Student

Hi, I am Michael Pergeorelis! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning and Computer Vision.
Contact Email

Michael Pergeorelis

Ph.D. Student

Hi, I am Huining Liang! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning and Computer Vision.
Contact Email

Huining Liang

Ph.D. Student

Hi, I am Yufan Wang! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning and Computer Vision.
Contact Email

Yufan Wang

Ph.D. Student

Hi, I am Daniela Martin! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning, Computer Vision, Remote Sensing and Astrophysics.
Contact Email

Daniela Martin

Ph.D. Student

Hi, I am Tyler Rust! I am a Ph.D. Student at the VIMS Lab. My research interests lie in 3D Reconstruction and Object Recognition.
LinkedIn

Tyler Rust

Ph.D. Student

Hi, I am Dara McNally! I am a Ph.D. Student at the VIMS Lab. My research interests lie in Deep Learning and Computer Vision.
Contact Email

Dara McNally

Ph.D. Student

Alumni

Photos


UD's provost visiting our lab for a demo. October, 2022


UD's provost trying out the lab's VR. October, 2022


Celebrating Yi Liu's graduation. June, 2022


At Yi Liu's graduation ceremony. June, 2022


Demos in the lab during the CIS alumni event. June, 2022


Current and past VIMS lab members meeting at CVPR. Long Beach, 2019


Resources




Computational resources


Two servers with 4xA6000 each

Two workstations with 2x3090 each

Three workstations with 4x2080Ti each

One workstation with 2x2080Ti

One workstation with 1x2080Ti and 1x1080Ti

One server with 2xPascal GPUs

Resources for students


PhD Program Policies

Miscellaneous

Contact Us


vims@cis.udel.edu
212 Smith Hall, Department of Computer & Information Sciences, University of Delaware, Newark DE 19716

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