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Seeing Roads Through Words: A Language-Guided Framework for RGB-T Driving Scene Segmentation
Ruturaj Reddy, Hrishav Bakul Barua, Junn Yong Loo +2
Robust semantic segmentation of road scenes under adverse illumination, lighting, and shadow conditions remain a core challenge for autonomous driving applications. RGB-Thermal fus…
Seeing in the Dark: A Teacher-Student Framework for Dark Video Action Recognition via Knowledge Distillation and Contrastive Learning
Sharana Dharshikgan Suresh Dass, Hrishav Bakul Barua, Ganesh Krishnasamy +2
Action recognition in dark or low-light (under-exposed) videos is a challenging task due to visibility degradation, which can hinder critical spatiotemporal details. This paper pro…
A Cycle Ride to HDR: Semantics Aware Self-Supervised Framework for Unpaired LDR-to-HDR Image Reconstruction
Hrishav Bakul Barua, Kalin Stefanov, Lemuel Lai En Che +3
Reconstruction of High Dynamic Range (HDR) from Low Dynamic Range (LDR) images is an important computer vision task. There is a significant amount of research utilizing both conven…
ActNetFormer: Transformer-ResNet Hybrid Method for Semi-Supervised Action Recognition in Videos
Sharana Dharshikgan Suresh Dass, Hrishav Bakul Barua, Ganesh Krishnasamy +2
Human action or activity recognition in videos is a fundamental task in computer vision with applications in surveillance and monitoring, self-driving cars, sports analytics, human…
GTA-HDR: A Large-Scale Synthetic Dataset for HDR Image Reconstruction
Hrishav Bakul Barua, Kalin Stefanov, KokSheik Wong +2
High Dynamic Range (HDR) content (i.e., images and videos) has a broad range of applications. However, capturing HDR content from real-world scenes is expensive and time-consuming.…
ArtHDR-Net: Perceptually Realistic and Accurate HDR Content Creation
Hrishav Bakul Barua, Ganesh Krishnasamy, KokSheik Wong +2
High Dynamic Range (HDR) content creation has become an important topic for modern media and entertainment sectors, gaming and Augmented/Virtual Reality industries. Many methods ha…