31 citations · 79 across the 18 of their papers we have counts for
18 papers
Monocular 3D Lane Detection via Structure Uncertainty-Aware Network with Curve-Point Queries
Ruixin Liu, Zejian Yuan
Monocular 3D lane detection is challenged by aleatoric uncertainty arising from inherent observation noise. Existing methods rely on simplified geometric assumptions, such as indep…
Flexible 3D Lane Detection by Hierarchical Shape MatchingFlexible 3D Lane Detection by Hierarchical Shape Matching
Zhihao Guan, Ruixin Liu, Zejian Yuan +6
As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict de…
Learning Segmented 3D Gaussians via Efficient Feature Unprojection for Zero-shot Neural Scene Segmentation
Bin Dou, Tianyu Zhang, Zhaohui Wang +2
Zero-shot neural scene segmentation, which reconstructs 3D neural segmentation field without manual annotations, serves as an effective way for scene understanding. However, existi…
An Efficient Wide-Range Pseudo-3D Vehicle Detection Using A Single Camera
Zhupeng Ye, Yinqi Li, Zejian Yuan
Wide-range and fine-grained vehicle detection plays a critical role in enabling active safety features in intelligent driving systems. However, existing vehicle detection methods b…
PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer
Ruijin Liu, Ning Lu, Dapeng Chen +3
We present PBFormer, an efficient yet powerful scene text detector that unifies the transformer with a novel text shape representation Polynomial Band (PB). The representation has…
Head-Tail Cooperative Learning Network for Unbiased Scene Graph Generation
Lei Wang, Zejian Yuan, Yao Lu +1
Scene Graph Generation (SGG) as a critical task in image understanding, facing the challenge of head-biased prediction caused by the long-tail distribution of predicates. However,…
End-to-end Lane Shape Prediction with Transformers
Ruijin Liu, Zejian Yuan, Tie Liu +1
Lane detection, the process of identifying lane markings as approximated curves, is widely used for lane departure warning and adaptive cruise control in autonomous vehicles. The p…
Domain Adaptation Gaze Estimation by Embedding with Prediction Consistency
Zidong Guo, Zejian Yuan, Chong Zhang +3
Gaze is the essential manifestation of human attention. In recent years, a series of work has achieved high accuracy in gaze estimation. However, the inter-personal difference limi…
Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation
Ziyang Song, Zejian Yuan, Chong Zhang +3
In recognition-based action interaction, robots' responses to human actions are often pre-designed according to recognized categories and thus stiff. In this paper, we specify a ne…
Attention-Oriented Action Recognition for Real-Time Human-Robot Interaction
Ziyang Song, Ziyi Yin, Zejian Yuan +4
Despite the notable progress made in action recognition tasks, not much work has been done in action recognition specifically for human-robot interaction. In this paper, we deeply…
Automatic Graphics Program Generation using Attention-Based Hierarchical Decoder
Zhihao Zhu, Zhan Xue, Zejian Yuan
Recent progress on deep learning has made it possible to automatically transform the screenshot of Graphic User Interface (GUI) into code by using the encoder-decoder framework. Wh…
Color naming guided intrinsic image decomposition
Yuanliu Liu, Zejian Yuan
Intrinsic image decomposition is a severely under-constrained problem. User interactions can help to reduce the ambiguity of the decomposition considerably. The traditional way of…
Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition
Yuanliu Liu, Ang Li, Zejian Yuan +2
We address the problem of decomposing a single image into reflectance and shading. The difficulty comes from the fact that the components of image---the surface albedo, the direct…
Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association
Dapeng Chen, Hongsheng Li, Xihui Liu +3
Person re-identification is an important task that requires learning discriminative visual features for distinguishing different person identities. Diverse auxiliary information ha…
Topic-Guided Attention for Image Captioning
Zhihao Zhu, Zhan Xue, Zejian Yuan
Attention mechanisms have attracted considerable interest in image captioning because of its powerful performance. Existing attention-based models use feedback information from the…
SymmNet: A Symmetric Convolutional Neural Network for Occlusion Detection
Ang Li, Zejian Yuan
Detecting the occlusion from stereo images or video frames is important to many computer vision applications. Previous efforts focus on bundling it with the computation of disparit…
Long-term Multi-granularity Deep Framework for Driver Drowsiness Detection
Jie Lyu, Zejian Yuan, Dapeng Chen
For real-world driver drowsiness detection from videos, the variation of head pose is so large that the existing methods on global face is not capable of extracting effective featu…
Learning Fixation Point Strategy for Object Detection and Classification
Jie Lyu, Zejian Yuan, Dapeng Chen
We propose a novel recurrent attentional structure to localize and recognize objects jointly. The network can learn to extract a sequence of local observations with detailed appear…