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Found 5 papers, 2 papers with code
Multimodal Adaptive Fusion of Face and Gait Features using Keyless attention based Deep Neural Networks for Human Identification
Biometrics plays a significant role in vision-based surveillance applications.
Co-segmentation Inspired Attention Module for Video-based Computer Vision Tasks
In this work, we propose to utilize the common rationale that a sequence of video frames capture a set of common objects and interactions between them, thus a notion of co-segmentation between the video frame features may equip the model with the ability to automatically focus on task-specific salient regions and improve the underlying task's performance in an end-to-end manner.
Face Age Progression With Attribute Manipulation
In this paper, we propose a novel holistic model in this regard viz., ``Face Age progression With Attribute Manipulation (FAWAM)", i. e. generating face images at different ages while simultaneously varying attributes and other subject specific characteristics.
Domain Adaptive Knowledge Distillation for Driving Scene Semantic Segmentation
Practical autonomous driving systems face two crucial challenges: memory constraints and domain gap issues.
Linguistically-aware Attention for Reducing the Semantic-Gap in Vision-Language Tasks
Humans perform such a correlation with a strong linguistic understanding of the visual world.
