| 2025 | AVSS | T-GAP: Temporal Granularity Aware Projection Network for Action Localization. | Himanshu Singh, Avijit Dey, Badri Narayan Subudhi, Vinit Jakhetiya, Thangaraj Veerakumar |
| 2025 | ICASSP | Graph Refinement in Latent Space: A Hypergraph Convolution for Underwater Object Detection. | Meghna Kapoor, Badri Narayan Subudhi, Ankur Bansal |
| 2024 | ICIP | Underwater Change Detection Using Multiple Sampling-Based Probabilistic Learner and Feature Preservance Discriminator. | Mehvish Nissar, Badri Narayan Subudhi, Vinit Jakhetiya, Amit Kumar Mishra |
| 2024 | ICPR | Principal Graph Neighborhood Aggregation for Underwater Moving Object Detection. | Meghna Kapoor, Badri Narayan Subudhi, Vinit Jakhetiya, Ankur Bansal |
| 2024 | ICPR | Project and Pool: An Action Localization Network for Localizing Actions in Untrimmed Videos. | Himanshu Singh, Avijit Dey, Badri Narayan Subudhi, Vinit Jakhetiya |
| 2023 | AAAI | Two-Streams: Dark and Light Networks with Graph Convolution for Action Recognition from Dark Videos (Student Abstract). | Saurabh Suman, Nilay Naharas, Badri Narayan Subudhi, Vinit Jakhetiya |
| 2023 | CVPR | Underwater Moving Object Detection using an End-to-End Encoder-Decoder Architecture and GraphSage with Aggregator and Refactoring. | Meghna Kapoor, Suvam Patra, Badri Narayan Subudhi, Vinit Jakhetiya, Ankur Bansal |
| 2022 | AVSS | An End to End Encoder-Decoder Network with Multi-scale Feature Pulling for Detecting Local Changes From Video Scene. | Manoj Kumar Panda, Badri Narayan Subudhi, Thierry Bouwmans, Vinit Jakheytiya, Thangaraj Veerakumar |
| 2020 | Tencon | Edge Preserving Image Fusion using Intensity Variation Approach. | Manoj Kumar Panda, Badri Narayan Subudhi, Thangaraj Veerakumar, Manoj Singh Gaur |
| 2013 | ICIP | Spatial constraint Hopfield-type neural networks for detecting changes in remotely sensed multitemporal images. | Badri Narayan Subudhi, Susmita Ghosh, Ashish Ghosh |
| 2012 | ISDA | Object and shadow separation using fuzzy Markov Random Field and local gray level co-occurence matrix based textural features. | Badri Narayan Subudhi, Susmita Ghosh, Ashish Ghosh |