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- Dataset Condensation with Distribution Matching507
This work proposes a simple yet effective method that synthesizes condensed images by matching feature distributions of the synthetic and original training images in many sampled embedding spaces and significantly reduces the synthesis cost while achieving comparable or better performance.
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- A survey on deep learning-based fine-grained object classification and semantic segmentation337
Four types of deep learning based fine-grained image classification approaches are reviewed, including the general convolutional neural networks (CNNs), part detection based, ensemble of networks based and visual attention based fine -grainedimage classification approaches.
- Review of Weed Detection Methods Based on Computer Vision303
This review elaborates the two aspects of using traditional image-processing methods and deep learning-based methods to solve weed detection problems and provides an overview of various methods for weed detection in recent years.
- MLVU: Benchmarking Multi-task Long Video Understanding294
A new benchmark called MLVU (Multitask Long Video Understanding Benchmark) is proposed for the comprehensive and in-depth evaluation of LVU, which suggests that factors such as context length, image-understanding ability, and the choice of LLM backbone can play critical roles in future advancements.
- Image Generation From Layout245
The proposed Layout2Im model significantly outperforms the previous state of the art, boosting the best reported inception score by 24.66% and 28.57% on the very challenging COCO-Stuff and Visual Genome datasets, respectively.
- SpatialBot: Precise Spatial Understanding with Vision Language Models220
SpatialBot, a model designed to enhance spatial understanding by utilizing both RGB and depth images, is proposed and the SpatialQA and SpatialQA $\boldsymbol{E}$ datasets are introduced to train VLMs for depth perception.
- Multi-View Image Generation from a Single-View193
This paper proposes a novel image generation model termed VariGANs, which combines the merits of the variational inference and the Generative Adversarial Networks (GANs), and generates the target image in a coarse-to-fine manner instead of a single pass which suffers from severe artifacts.
- Neural Person Search Machines171
Evaluations on two benchmark datasets have demonstrated that the Neural Person Search Machines (NPSM) developed can outperform current state-of-the-arts in both mAP and top-1 evaluation protocols.
- CAFE: Learning to Condense Dataset by Aligning Features170
This paper proposes a novel scheme to Condense dataset by Aligning FEatures (CAFE), which explicitly attempts to preserve the real-feature distribution as well as the discriminant power of the resulting synthetic set, lending itself to strong generalization capability to various architectures.
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- Development of a tomato harvesting robot used in greenhouse111
Some insights are provided into the development and application of tomato harvesting robot used in the greenhouse and obstacle avoidance strategies proposed based on the C-space method.
- Enhancement of Detecting Permanent Water and Temporary Water in Flood Disasters by Fusing Sentinel-1 and Sentinel-2 Imagery Using Deep Learning Algorithms: Demonstration of Sen1Floods11 Benchmark Datasets109
This paper proposes an automatic segmentation method for surface water, permanent water, and temporary water identification, and all tasks share the same convolutional neural network architecture and utilizes focal loss to deal with the class (water/non-water) imbalance problem.
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- Interpretable Spatio-Temporal Attention for Video Action Recognition97
This model not only improves video action recognition accuracy, but also localizes discriminative regions both spatially and temporally, despite being trained in a weakly-supervised manner with only classification labels (no bounding box labels or time frame temporal labels).
- Left-Right Comparative Recurrent Model for Stereo Matching89
A novel left- right comparative recurrent model to perform left-right consistency checking jointly with disparity estimation and a soft attention mechanism is introduced, which employs the learned error maps for better guiding the model to selectively focus on refining the unreliable regions at the next recurrent step.
- CT synthesis from MR in the pelvic area using Residual Transformer Conditional GAN85
A new GAN called Residual Transformer Conditional GAN (RTCGAN), which exploits the advantages of CNN in local texture details and Transformer in global correlation to extract multi-level features from MR and CT images and achieves desirable results on local mismatch tissues.
- Weed and Corn Seedling Detection in Field Based on Multi Feature Fusion and Support Vector Machine82
The experimental results showed that the fusion feature combination of rotation invariant LBP feature and gray level-gradient co-occurrence matrix based on SVM classifier obtained the highest classification accuracy and accurately detected all kinds of weeds and corn seedlings.
- Modular Generative Adversarial Networks82
ModularGAN consists of several reusable and composable modules that carry on different functions that can be trained simultaneously, leveraging data from all domains, and then combined to construct specific GAN networks at test time, according to the specific image translation task.
- Application of Convolutional Neural Network-Based Detection Methods in Fresh Fruit Production: A Comprehensive Review80
Improved CNN deep learning models can give full play to detection potential by combining with the characteristics of each link of fruit production, and imply that CNN-based detection may penetrate the challenges created by environmental issues, new area exploration, and multiple task execution of fresh fruit production in the future.
- Automatic generation of large-scale handwriting fonts via style learning79
Using the proposed system, for the first time the practical handwriting font library in a user's personal style with arbitrarily large numbers of Chinese characters can be generated automatically.
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- Minimal mask immobilization with optical surface guidance for head and neck radiotherapy61
These pilot results confirm feasibility of minimal mask immobilization combined with commercially available optical image guidance and follow‐up validation, with direct comparison to standardMask immobilization, appears warranted.
- EasyFont59
Using the proposed EasyFont system, for the first time, the practical handwriting font library in a user’s personal style with arbitrarily large numbers of Chinese characters can be generated automatically.
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 2026-10-15. 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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