8 papers
Inference-time Stochastic Refinement of GRU-Normalizing Flow for Real-time Video Motion Transfer
Tasmiah Haque, Srinjoy Das
Real-time video motion transfer applications such as immersive gaming and vision-based anomaly detection require accurate yet diverse future predictions to support realistic synthe…
Post-Training Quantization of Generative and Discriminative LSTM Text Classifiers: A Study of Calibration, Class Balance, and Robustness
Md Mushfiqur Rahaman, Elliot Chang, Tasmiah Haque +1
Text classification plays a pivotal role in edge computing applications like industrial monitoring, health diagnostics, and smart assistants, where low latency and high accuracy ar…
Path Generation and Evaluation in Video Games: A Nonparametric Statistical Approach
Daniel Campa, Mehdi Saeedi, Ian Colbert +1
Navigation path traces play a crucial role in video game design, serving as a vital resource for both enhancing player engagement and fine-tuning non-playable character behavior. G…
GIF: Generative Inspiration for Face Recognition at Scale
Saeed Ebrahimi, Sahar Rahimi, Ali Dabouei +3
Aiming to reduce the computational cost of Softmax in massive label space of Face Recognition (FR) benchmarks, recent studies estimate the output using a subset of identities. Alth…
Towards Efficient Real-Time Video Motion Transfer via Generative Time Series Modeling
Tasmiah Haque, Md. Asif Bin Syed, Byungheon Jeong +5
Motion Transfer is a technique that synthesizes videos by transferring motion dynamics from a driving video to a source image. In this work we propose a deep learning-based framewo…
LNUCB-TA: Linear-nonlinear Hybrid Bandit Learning with Temporal Attention
Hamed Khosravi, Mohammad Reza Shafie, Ahmed Shoyeb Raihan +2
Existing contextual multi-armed bandit (MAB) algorithms fail to effectively capture both long-term trends and local patterns across all arms, leading to suboptimal performance in e…