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Found 11 papers, 5 papers with code
Channel and Spatial Relation-Propagation Network for RGB-Thermal Semantic Segmentation
In this paper, we propose a Channel and Spatial Relation-Propagation Network (CSRPNet) for RGB-T semantic segmentation, which propagates only modality-shared information across different modalities and alleviates the modality-specific information contamination issue.
Ranked #12 on
Thermal Image Segmentation
on PST900
Reliability-Hierarchical Memory Network for Scribble-Supervised Video Object Segmentation
To be specific, RHMNet first only uses the memory in the high-reliability level to locate the region with high reliability belonging to the target, which is highly similar to the initial target scribble.
Global Tracking via Ensemble of Local Trackers
While it can exploit the temporal context like historical appearances and locations of the target, a potential limitation of such strategy is that the local tracker tends to misidentify a nearby distractor as the target instead of activating the re-detector when the real target is out of view.
GroupTransNet: Group Transformer Network for RGB-D Salient Object Detection
The features of the intermediate process are first fused by the features of different layers, and then processed by several transformers in multiple groups, which not only makes the size of the features of each scale unified and interrelated, but also achieves the effect of sharing the weight of the features within the group.
Near-Optimal 3-D Visual Coverage for Quadrotor Unmanned Aerial Vehicles Under Photogrammetric Constraints
In this article, we propose a complete visual coverage trajectory planning framework for quadrotor un- manned aerial vehicles (UAVs) in three-dimensional (3-D) terrain environment under photogrammetric constraints.
LC3Net: Ladder context correlation complementary network for salient object detection
Currently, existing salient object detection methods based on convolutional neural networks commonly resort to constructing discriminative networks to aggregate high level and low level features.
CCTrans: Simplifying and Improving Crowd Counting with Transformer
However, the transformer can model the global context easily.
M2RNet: Multi-modal and Multi-scale Refined Network for RGB-D Salient Object Detection
The adjacent interactive aggregation module (AIAM) gradually integrates the neighbor features of high, middle and low levels.
Saliency-Associated Object Tracking
A potential limitation of such trackers is that not all patches are equally informative for tracking.
AMRNet: Chips Augmentation in Aerial Images Object Detection
Specifically, we propose a scale adaptive module, which dynamically adjusts chip size to balance object scale, narrowing scale variation in training.
Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
These two similarities complement each other and hence enhance the discriminative capacity of the network for handling distractors.
