1 citations · 1 across the 1 of their papers we have counts for
6 papers
Recursive Training for Zero-Shot Semantic Segmentation
Ce Wang, Moshiur Farazi, Nick Barnes
General purpose semantic segmentation relies on a backbone CNN network to extract discriminative features that help classify each image pixel into a 'seen' object class (ie., the o…
Efficient Two-Stream Network for Violence Detection Using Separable Convolutional LSTM
Zahidul Islam, Mohammad Rukonuzzaman, Raiyan Ahmed +2
Automatically detecting violence from surveillance footage is a subset of activity recognition that deserves special attention because of its wide applicability in unmanned securit…
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds
Sameera Ramasinghe, Moshiur Farazi, Salman Khan +2
Conditional GANs (cGAN), in their rudimentary form, suffer from critical drawbacks such as the lack of diversity in generated outputs and distortion between the latent and output m…
Attention Guided Semantic Relationship Parsing for Visual Question Answering
Moshiur Farazi, Salman Khan, Nick Barnes
Humans explain inter-object relationships with semantic labels that demonstrate a high-level understanding required to perform complex Vision-Language tasks such as Visual Question…
Accuracy vs. Complexity: A Trade-off in Visual Question Answering Models
Moshiur R. Farazi, Salman H. Khan, Nick Barnes
Visual Question Answering (VQA) has emerged as a Visual Turing Test to validate the reasoning ability of AI agents. The pivot to existing VQA models is the joint embedding that is…
From Known to the Unknown: Transferring Knowledge to Answer Questions about Novel Visual and Semantic Concepts
Moshiur R Farazi, Salman H Khan, Nick Barnes
Current Visual Question Answering (VQA) systems can answer intelligent questions about `Known' visual content. However, their performance drops significantly when questions about v…