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- Jingyu YangSuggested from co-authorship
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Works277 from public data
- 542
- TokenPose: Learning Keypoint Tokens for Human Pose Estimation418
A novel approach based on Token representation for human Pose estimation (TokenPose), in detail, each keypoint is explicitly embedded as a token to simultaneously learn constraint relationships and appearance cues from images.
- TransPose: Keypoint Localization via Transformer417
This work proposes a model called Trans-Pose, which introduces Transformer for human pose estimation, and the attention layers built in Transformer enable the model to capture long-range relationships efficiently and also can reveal what dependencies the predicted key-points rely on.
- SimCC: A Simple Coordinate Classification Perspective for Human Pose Estimation248
The proposed SimCC uniformly divides each pixel into several bins, thus achieving sub-pixel localization precision and low quantization error, and can omit additional refinement post-processing and exclude upsampling layers under certain settings, resulting in a more simple and effective pipeline for HPE.
- 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.
- Correlation-Aware Deep Tracking200
This work proposes a novel target-dependent feature network inspired by the self-/cross-attention scheme that deeply embeds cross-image feature correlation in multiple layers of the feature network and is able to suppress non-target features, resulting in instance-varying feature extraction.
- 184
- A multi-manifold discriminant analysis method for image feature extraction184
A Multi-Manifold Discriminant Analysis method based on graph embedded learning and under the Fisher discriminant analysis framework is proposed, leading to promising image recognition performance.
- Kernel sparse representation based classification161
A kernel sparse representation based classification (KSRC) algorithm is proposed, which has more powerful classification ability than SRC and is demonstrated to be effective in face recognition, palmprint recognition and finger-knuckle-print recognition.
- A collaborative representation based projections method for feature extraction160
Experimental results on FERET, AR, Yale face databases and the PolyU finger-knuckle-print database demonstrate that CRP works well in feature extraction and leads to a good recognition performance.
- Vision-Based UAV Self-Positioning in Low-Altitude Urban Environments140
A new dataset, DenseUAV, that is the first publicly available dataset tailored for the UAV self-positioning task and incorporates metric learning into representation learning to enhance the model’s discriminative capacity and to reduce the modality discrepancy.
- 130
- The Ninth Visual Object Tracking VOT2021 Challenge Results127
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative; results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years.
- 121
- Learning robust and discriminative low-rank representations for face recognition with occlusion114
This paper proposes a novel method by exploiting the low-rankness of both the data representation and each occlusion-induced error image simultaneously, by which the global structure of data together with the error images can be well captured.
- Support vector machine-based optimized decision threshold adjustment strategy for classifying imbalanced data112
The proposed strategy is self-adapting and can find the optimal moving distance of the classification hyperplane according to the real distributions of training samples and is extended to develop an ensemble version (EnSVM-OTHR) that can further improve the classification performance.
- 106
- Learning Tracking Representations via Dual-Branch Fully Transformer Networks76
A Siamese-like Dual-branch network based on solely Transformers for tracking, which outperforms the state-of-the-art methods on the GOT-10k and VOT2020 benchmarks and achieves real-time inference speed (about 40 fps) on one GPU.
- Face recognition using adaptive local ternary patterns method70
An adaptive local feature descriptor for face recognition based on an automatic strategy selecting the threshold for LTP and CS-LBP is introduced and a center-symmetric adaptive local ternary pattern (CS-ALTP) feature description method forFace recognition is proposed.
- Feature extraction based on Laplacian bidirectional maximum margin criterion68
A novel criterion, namely Laplacian bidirectional maximum margin criterion (LBMMC), is developed to address the issue of discriminative information within the local structures of samples and the structural information embedding in the images.
- ADNet: Lane Shape Prediction via Anchor Decomposition66
This paper revisits the limitations of anchor-based lane detection methods and introduces the Large Kernel Attention for Feature Pyramid Network (FPN) and the General Lane IoU (GLIoU) loss, which significantly improves the performance of ADNet in complex scenarios.
- 65
- A multi-task Faster R-CNN method for 3D vehicle detection based on a single image57
A 3D vehicle detection method using a single image is proposed to generate the 3D space coordinate information of the object using monocular vision for autonomous driving and is named multi-task Faster R- CNN (MT-Faster R-CNN).
- A local multiple patterns feature descriptor for face recognition57
A local multiple patterns feature descriptor based on the Weber's law for feature extraction and face recognition and a multi-scale block LMP is presented to generate more discriminative and robust visual feature.
- Hourly solar irradiance forecasting based on encoder–decoder model using series decomposition and dynamic error compensation56
The experimental results indicate that the proposed model shows accurate and robust forecasting performance and is a reliable alternative to hourly irradiance forecasting.
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 2026-10-14. 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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