RGB–thermal (RGB-T) salient object detection exploits complementary cues from visible and thermal sensors to maintain reliable performance in adverse environments. However, many existing methods (i) fuse modalities before sufficiently enhancing intra-modal semantics and (ii) are sensitive to modality discrepancies caused by heterogeneous sensor characteristics. To address these issues, we propose PACNet (Pyramid Attention Collaboration Network), a hierarchical RGB-T framework that jointly models multi-scale and global context and performs refinement-before-fusion with cross-modal collaboration. Specifically, Dense Atrous Spatial Pyramid Pooling (DASPP) captures multi-scale contextual cues... More >

Video summarization (VS) aims to generate concise representations of long videos by extracting the most informative frames while maintaining essential content. Existing methods struggle to capture multi-scale dependencies and often rely on suboptimal feature representations, limiting their ability to model complex inter-frame relationships. To address these issues, we propose a multi-scale sensing network that incorporates three key innovations to improve VS. First, we introduce multi-scale dilated convolution blocks with progressively increasing dilation rates to capture temporal context at multiple levels, enabling the network to understand both local transitions and long-range dependencie... More >

The proliferation of deepfake technology poses significant threats to digital media authenticity, necessitating robust detection systems to combat manipulated content. This paper presents a novel attention-based framework for deepfake detection that systematically integrates multiple complementary attention mechanisms to enhance discriminative feature learning. Our approach combines spatial attention, multi-head self-attention, and channel attention modules with a VGG-16 backbone to capture comprehensive representations across different feature spaces. The spatial attention mechanism focuses on discriminative facial regions, while multi-head self-attention captures long-range spatial depende... More >