6 citations · 8 across the 9 of their papers we have counts for
11 papers
Mapping the Concept Landscape: Structural Perception of Global Distributions for Transparent Data Pruning
Dongyue Wu, Tao Ma
Existing data pruning methods predominantly rely on high-dimensional feature embeddings to measure sample importance. However, these compressed vectors often obscure fine-grained s…
Achieving Text-based Person Retrieval with Any Granularity
Jialong Zuo, Hanyu Zhou, Dongyue Wu +5
Text-based person retrieval faces a critical but under-explored challenge: the inherent uncertainty of query granularity in real-world scenarios. This paper introduces a new paradi…
Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
Dongyue Wu, Zilin Guo, Xiaoyu Li +4
The rapid growth of modern training datasets has significantly increased computational cost, motivating dataset pruning~(DP) methods which retain only a subset of informative sampl…
Partial Forward Blocking: A Novel Data Pruning Paradigm for Lossless Training Acceleration
Dongyue Wu, Zilin Guo, Jialong Zuo +2
The ever-growing size of training datasets enhances the generalization capability of modern machine learning models but also incurs exorbitant computational costs. Existing data pr…
ReID5o: Achieving Omni Multi-modal Person Re-identification in a Single Model
Jialong Zuo, Yongtai Deng, Mengdan Tan +5
In real-word scenarios, person re-identification (ReID) expects to identify a person-of-interest via the descriptive query, regardless of whether the query is a single modality or…
Object-Aware Video Matting with Cross-Frame Guidance
Huayu Zhang, Dongyue Wu, Yuanjie Shao +2
Recently, trimap-free methods have drawn increasing attention in human video matting due to their promising performance. Nevertheless, these methods still suffer from the lack of d…
Structural Pruning via Spatial-aware Information Redundancy for Semantic Segmentation
Dongyue Wu, Zilin Guo, Li Yu +2
In recent years, semantic segmentation has flourished in various applications. However, the high computational cost remains a significant challenge that hinders its further adoptio…
Adaptive Prototype Replay for Class Incremental Semantic Segmentation
Guilin Zhu, Dongyue Wu, Changxin Gao +3
Class incremental semantic segmentation (CISS) aims to segment new classes during continual steps while preventing the forgetting of old knowledge. Existing methods alleviate catas…
Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
Xiangheng Shan, Dongyue Wu, Guilin Zhu +3
Open-vocabulary semantic segmentation is a challenging task, which requires the model to output semantic masks of an image beyond a close-set vocabulary. Although many efforts have…
SCTNet: Single-Branch CNN with Transformer Semantic Information for Real-Time Segmentation
Zhengze Xu, Dongyue Wu, Changqian Yu +3
Recent real-time semantic segmentation methods usually adopt an additional semantic branch to pursue rich long-range context. However, the additional branch incurs undesirable comp…
Semantic Segmentation via Pixel-to-Center Similarity Calculation
Dongyue Wu, Zilin Guo, Aoyan Li +3
Since the fully convolutional network has achieved great success in semantic segmentation, lots of works have been proposed focusing on extracting discriminative pixel feature repr…