The model in this paper is a three-branch model including raw branch, object branch and part branch. The images are fed directly into the raw branch. Coordinate Attention Object Localization Module (CAOLM) is used to localize and crop objects in the image to generate the input for the ...
"Enhancing Thermal Infrared Tracking with Natural Language Modeling and Coordinate Sequence Generation." ArXiv (2024). [paper] [code] Yang Luo, Xiqing Guo, Hao Li. "From Two-Stream to One-Stream: Efficient RGB-T Tracking via Mutual Prompt Learning and Knowledge Distillation." ArXiv (2024). ...
Furthermore, agents can communicate more specific information, such as in GAXNet [79], where agents coordinate their local attention weights, integrating hidden states from neighboring agents. Messages can also be modeled as random variables, as seen in NDQ [74], where messages are drawn from a...
The nth branch of any nth stage has the smallest heatmap resolution size and largest number of channels for that stage. We take advantage of this feature to properly compress the spatial information in the channel, perform dense modeling, and restore the resolution of the heatmap by upsampling...
Besides, in order to generate feature maps with high quality, a novel residual dense block with coordinate attention is proposed. In addition to reducing gradient explosion and gradient disappearance, it can reduce the number of parameters by 5.3 times compared to the original feature pyramid ...
level semantic information. Towards the end of the backbone, a Spatial Pyramid Pooling-Fast (SPPF) module is integrated. It establishes multi-branch, multi-scale pooling layers to create and amalgamate features of varied scales, thereby enhancing the network’s multi-scale feature representation ...
1. The framework is composed of two branches: the 3D Geometric branch and the 2D Texture branch. The input of the 3D Geometric branch is a 3D point cloud that can be obtained directly from a lidar sensor or using the depth information and the intrinsic camera parameters of an RGB-D ...
To further reveal how multiple genes coordinate to regulate SCC, we analyzed the gene modules identified in two developmental stages ofB. napusseeds to elucidate the putative regulatory mechanisms of SCC. At 20 DAF, only one significant component (the corresponding gene module was termed M65) was ...
positional variations between predicted boxes and ground-truth boxes are quantified using the coordinate loss. Given the nature of object detection tasks, it is crucial to consider target confidence, classification, and position information. The following shows the computation of the overall loss ...
ACNet extracts image features by balancing the distribution of features through ACM (Attention Complementary Modules) and adding a third branch. The SE (Squeeze and Excitation) module is used first for feature extraction, followed by the additive fusion. Except for the fusion mode, the other ...