Neelanjan Bhowmik — accepted AI-conference papers

2024

Towards Open-World Object-based Anomaly Detection via Self-Supervised Outlier Synthesis

Brian Kostadinov Shalon Isaac-Medina*, Yona Falinie Abdul Gaus*, Neelanjan Bhowmik, Toby P Breckon

ECCV 2024poster

"Object detection is a pivotal task in computer vision that has received significant attention in previous years. Nonetheless, the capability of a detector to localise objects out of the training distribution remains unexplored. Whilst recent approaches in object-level out-of-distribution (OoD) dete…

Cited by 2 Source ↗PDF ↗code ↗Scholar ↗

2023

Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers

Abril Corona-Figueroa, Sam Bond-Taylor, Neelanjan Bhowmik, Yona Falinie A. Gaus, Toby P. Breckon, Hubert P. H. Shum +1

ICCV 2023poster

Generating 3D images of complex objects conditionally from a few 2D views is a difficult synthesis problem, compounded by issues such as domain gap and geometric misalignment. For instance, a unified framework such as Generative Adversarial Networks cannot achieve this unless they explicitly define…

Cited by 7 PDF ↗code ↗Scholar ↗