98 citations · 232 across the 25 of their papers we have counts for
25 papers
Unsupervised Domain Adaptation via Domain-Adaptive Diffusion
Duo Peng, Qiuhong Ke, Yinjie Lei +1
Unsupervised Domain Adaptation (UDA) is quite challenging due to the large distribution discrepancy between the source domain and the target domain. Inspired by diffusion models wh…
Unsupervised Image Denoising in Real-World Scenarios via Self-Collaboration Parallel Generative Adversarial Branches
Xin Lin, Chao Ren, Xiao Liu +2
Deep learning methods have shown remarkable performance in image denoising, particularly when trained on large-scale paired datasets. However, acquiring such paired datasets for re…
End-to-End 3D Dense Captioning with Vote2Cap-DETR
Sijin Chen, Hongyuan Zhu, Xin Chen +3
3D dense captioning aims to generate multiple captions localized with their associated object regions. Existing methods follow a sophisticated ``detect-then-describe'' pipeline equ…
ZegCLIP: Towards Adapting CLIP for Zero-shot Semantic Segmentation
Ziqin Zhou, Bowen Zhang, Yinjie Lei +2
Recently, CLIP has been applied to pixel-level zero-shot learning tasks via a two-stage scheme. The general idea is to first generate class-agnostic region proposals and then feed…
Pretrained Language Encoders are Natural Tagging Frameworks for Aspect Sentiment Triplet Extraction
Yanjie Gou, Yinjie Lei, Lingqiao Liu +3
Aspect Sentiment Triplet Extraction (ASTE) aims to extract the spans of aspect, opinion, and their sentiment relations as sentiment triplets. Existing works usually formulate the s…
Semantic-Aware Domain Generalized Segmentation
Duo Peng, Yinjie Lei, Munawar Hayat +2
Deep models trained on source domain lack generalization when evaluated on unseen target domains with different data distributions. The problem becomes even more pronounced when we…
Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds
Zhao Jin, Yinjie Lei, Naveed Akhtar +2
Point cloud scene flow estimation is of practical importance for dynamic scene navigation in autonomous driving. Since scene flow labels are hard to obtain, current methods train t…
Box2Seg: Learning Semantics of 3D Point Clouds with Box-Level Supervision
Yan Liu, Qingyong Hu, Yinjie Lei +3
Learning dense point-wise semantics from unstructured 3D point clouds with fewer labels, although a realistic problem, has been under-explored in literature. While existing weakly…
Mind Your Clever Neighbours: Unsupervised Person Re-identification via Adaptive Clustering Relationship Modeling
Lianjie Jia, Chenyang Yu, Xiehao Ye +3
Unsupervised person re-identification (Re-ID) attracts increasing attention due to its potential to resolve the scalability problem of supervised Re-ID models. Most existing unsupe…
Overcome Anterograde Forgetting with Cycled Memory Networks
Jian Peng, Dingqi Ye, Bo Tang +3
Learning from a sequence of tasks for a lifetime is essential for an agent towards artificial general intelligence. This requires the agent to continuously learn and memorize new k…
Reviewing continual learning from the perspective of human-level intelligence
Yifan Chang, Wenbo Li, Jian Peng +7
Humans' continual learning (CL) ability is closely related to Stability Versus Plasticity Dilemma that describes how humans achieve ongoing learning capacity and preservation for l…
Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation
Duo Peng, Yinjie Lei, Wen Li +2
Domain adaptation is critical for success when confronting with the lack of annotations in a new domain. As the huge time consumption of labeling process on 3D point cloud, domain…
Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentation
Duo Peng, Yinjie Lei, Lingqiao Liu +2
Semantic segmentation is a crucial image understanding task, where each pixel of image is categorized into a corresponding label. Since the pixel-wise labeling for ground-truth is…
A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
Wei Liu, Pingping Zhang, Yinjie Lei +3
Image smoothing is a fundamental procedure in applications of both computer vision and graphics. The required smoothing properties can be different or even contradictive among diff…
Hierarchical Paired Channel Fusion Network for Street Scene Change Detection
Yinjie Lei, Duo Peng, Pingping Zhang +2
Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging ta…
Contextualize Knowledge Bases with Transformer for End-to-end Task-Oriented Dialogue Systems
Yanjie Gou, Yinjie Lei, Lingqiao Liu +2
Incorporating knowledge bases (KB) into end-to-end task-oriented dialogue systems is challenging, since it requires to properly represent the entity of KB, which is associated with…
Semi-Supervised Crowd Counting via Self-Training on Surrogate Tasks
Yan Liu, Lingqiao Liu, Peng Wang +2
Most existing crowd counting systems rely on the availability of the object location annotation which can be expensive to obtain. To reduce the annotation cost, one attractive solu…
Towards Using Count-level Weak Supervision for Crowd Counting
Yinjie Lei, Yan Liu, Pingping Zhang +1
Most existing crowd counting methods require object location-level annotation, i.e., placing a dot at the center of an object. While being simpler than the bounding-box or pixel-le…
Improving Distant Supervised Relation Extraction by Dynamic Neural Network
Yanjie Gou, Yinjie Lei, Lingqiao Liu +2
Distant Supervised Relation Extraction (DSRE) is usually formulated as a problem of classifying a bag of sentences that contain two query entities, into the predefined relation cla…
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic Consolidation
Jian Peng, Bo Tang, Hao Jiang +4
Artificial neural networks face the well-known problem of catastrophic forgetting. What's worse, the degradation of previously learned skills becomes more severe as the task sequen…
Deep Multiphase Level Set for Scene Parsing
Pingping Zhang, Wei Liu, Yinjie Lei +2
Recently, Fully Convolutional Network (FCN) seems to be the go-to architecture for image segmentation, including semantic scene parsing. However, it is difficult for a generic FCN…
Cascaded Context Pyramid for Full-Resolution 3D Semantic Scene Completion
Pingping Zhang, Wei Liu, Yinjie Lei +2
Semantic Scene Completion (SSC) aims to simultaneously predict the volumetric occupancy and semantic category of a 3D scene. It helps intelligent devices to understand and interact…
A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
Wei Liu, Pingping Zhang, Yinjie Lei +3
Image smoothing is a fundamental procedure in applications of both computer vision and graphics. The required smoothing properties can be different or even contradictive among diff…
A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning
Yinjie Lei, Ziqin Zhou, Pingping Zhang +3
A sketch based 3D shape retrieval