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- 3,850
- Res2Net: A New Multi-Scale Backbone Architecture3,450
This paper proposes a novel building block for CNNs, namely Res2Net, by constructing hierarchical residual-like connections within one single residual block that represents multi-scale features at a granular level and increases the range of receptive fields for each network layer.
- Attention mechanisms in computer vision: A survey2,538
This survey provides a comprehensive review of various attention mechanisms in computer vision and categorize them according to approach, such as channel attention, spatial attention, temporal attention, and branch attention.
- 2,466
- Structure-Measure: A New Way to Evaluate Foreground Maps1,970
A novel, efficient, and easy to calculate measure known as S-measure (structural measure) to evaluate foreground maps, which simultaneously evaluates region-aware and object-aware structural similarity between a foreground map and a ground-truth map.
- 1,938
- Enhanced-alignment Measure for Binary Foreground Map Evaluation1,716
This paper takes a detailed look at current binary FM evaluation measures and proposes a novel and effective E-measure (Enhanced-alignment measure), jointly capturing image-level statistics and local pixel matching information, which demonstrates the superiority of this measure over the available measures on 4 popular datasets via 5 meta-measures.
- Deeply Supervised Salient Object Detection with Short Connections1,458
This paper proposes a new salient object detection method by introducing short connections to the skip-layer structures within the HED architecture, which takes full advantage of multi-level and multi-scale features extracted from FCNs, providing more advanced representations at each layer, a property that is critically needed to perform segment detection.
- Richer Convolutional Features for Edge Detection1,240
RCF encapsulates all convolutional features into more discriminative representation, which makes good usage of rich feature hierarchies, and is amenable to training via backpropagation, and achieves state-of-the-art performance on several available datasets.
- EGNet: Edge Guidance Network for Salient Object Detection1,212
This paper presents an edge guidance network (EGNet) for salient object detection with three steps to simultaneously model these two kinds of complementary information in a single network to solve the complementarity between salient edge information and salient object information.
- A Simple Pooling-Based Design for Real-Time Salient Object Detection1,145
This work solves the problem of salient object detection by investigating how to expand the role of pooling in convolutional neural networks by building a global guidance module (GGM) and designing a feature aggregation module (FAM) to make the coarse-level semantic information well fused with the fine-level features from the top-down path- way.
- Visual attention network1,121
This paper proposes a novel linear attention named large kernel attention (LKA) to enable self-adaptive and long-range correlations in self-attention while avoiding its shortcomings, and presents a neural network based on LKA, namely Visual Attention Network (VAN).
- 1,085
- 1,021
- 939
- 915
- Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach900
This work investigates a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems and proposes a new adversarial erasing approach for localizing and expanding object regions progressively.
- Large Selective Kernel Network for Remote Sensing Object Detection850
This paper considers these priors and proposes the lightweight Large Selective Kernel Network (LSKNet), which can dynamically adjust its large spatial receptive field to better model the ranging context of various objects in remote sensing scenarios.
- Strip Pooling: Rethinking Spatial Pooling for Scene Parsing817
Beyond conventional spatial pooling that usually has a regular shape of NxN, a new pooling strategy is introduced, called strip pooling, which considers a long but narrow kernel, i.e., 1xN or Nx1.
- 790
- Concealed Object Detection786
The first systematic study on concealed object detection (COD), which aims to identify objects that are visually embedded in their background, is presented, and rich annotations including object categories, object boundaries, challenging attributes, object-level labels, and instance-level annotations are provided.
- Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks729
It is demonstrated that D3Net can be used to efficiently extract salient object masks from real scenes, enabling effective background-changing application with a speed of 65 frames/s on a single GPU.
- Sketch2Photo706
A system that composes a realistic picture from a simple freehand sketch annotated with text labels, able to automatically select suitable photographs to generate a high quality composition, using a filtering scheme to exclude undesirable images.
- Low-Light Image and Video Enhancement Using Deep Learning: A Survey651
This paper proposes a low-light image and video dataset, in which the images and videos are taken by different mobile phones’ cameras under diverse illumination conditions, and provides a unified online platform that covers many popular LLIE methods.
- 638
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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