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Claim this profileWorks139 from public data
- An integrated UGV-UAV system for construction site data collection232
This paper designs a UAV-UGV team that integrates two custom-built mobile robots that is capable of autonomous navigation, and the performance of the system demonstrates the feasibility of developing and deploying a robust and automated data collection system for construction applications in the near future.
- Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection202
The key idea is that with the annotated 3D bounding boxes of objects in an image, there is a rich set of well-posed projected 2D supervision signals available in training, such as the projected corner keypoints and their associated offset vectors with respect to the center of 2D bounders, which should be exploited as auxiliary tasks in training.
- Image Synthesis From Reconfigurable Layout and Style166
This paper presents a layout- and style-based architecture for generative adversarial networks (termed LostGANs) that can be trained end-to-end to generate images from reconfigurable layout and style.
- Learning Attraction Field Representation for Robust Line Segment Detection161
A region-partition based attraction field dual representation for line segment maps, which poses the problem of line segment detection (LSD) as the region coloring problem and harnesses the best practices developed in ConvNets based semantic segmentation methods such as the encoder-decoder architecture and the a-trous convolution.
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- A stochastic graph grammar for compositional object representation and recognition140
A hierarchical generative model for representing and recognizing compositional object categories with large intra-category variance that combines the power of a stochastic context free grammar (SCFG) to express the variability of part configurations, and a Markov random field (MRF) to represent the pictorial spatial relationships between these parts.
- Holistically-Attracted Wireframe Parsing138
This paper presents a fast and parsimonious parsing method to accurately and robustly detect a vectorized wireframe in an input image with a single forward pass, and is thus called Holistically-Attracted Wireframe Parser (HAWP).
- Face Detection with End-to-End Integration of a ConvNet and a 3D Model132
This paper presents a method for face detection in the wild, which integrates a ConvNet and a 3D mean face model in an end-to-end multi-task discriminative learning framework and addresses two issues in adapting state-of-the-art generic object detection ConvNets.
- Vision-based integrated mobile robotic system for real-time applications in construction128
This paper proposes a mobile robotic platform that incorporates a stack of embedded platforms with integrated Graphical Processing Units (GPUs) to demonstrate the robustness and feasibility of developing and deploying an autonomous system in the near future.
- Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis97
An intuitive paradigm for the task, layout-to-mask- to-image, which learns to unfold object masks in a weakly-supervised way based on an input layout and object style codes is proposed and a method built on Generative Adversarial Networks (GANs) is presented.
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- Online Object Tracking, Learning and Parsing with And-Or Graphs82
Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability.
- Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model81
A method of learning reconfigurable hierarchical And-Or models to integrate context and occlusion for car detection using Weak-Label Structural SVM and compares with state-of-the-art variants of deformable part-based models and other methods.
- Sign-Based Gradient Descent With Heterogeneous Data: Convergence and Byzantine Resilience75
A novel magnitude-driven stochastic-sign-based gradient compressor is proposed to address the non-convergence issue of SignSGD, and the convergence of the proposed method is established in the presence of arbitrary data heterogeneity.
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- Recognizing Car Fluents from Video53
A spatial-temporal And-Or hierarchical model to represent car fluents is formulated under the latent structural SVM framework and outperforms several highly related baseline methods in terms of car fluent recognition and car part localization.
- PlaneTR: Structure-Guided Transformers for 3D Plane Recovery52
A neural network built upon Transformers, namely PlaneTR, to simultaneously detect and reconstruct planes from a single image and achieves state-of-the-art performance on the ScanNet and NYUv2 datasets.
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- Learning Local-Global Contextual Adaptation for Multi-Person Pose Estimation45
This paper proposes a multi-person pose estimation approach, dubbed as LOGO-CAP, by learning the LOcal-GlObal Contextual Adaptation for human Pose, which is end-to-end trainable with near real-time inference speed in a single forward pass, obtaining state-of-the-art performance on the COCO keypoint benchmark for bottom-up human pose estimation.
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- CGBA: Curvature-aware Geometric Black-box Attack42
A novel query-efficient curvature-aware geometric decision-based black-box attack that conducts boundary search along a semicircular path on a restricted 2D plane to ensure finding a boundary point successfully irrespective of the boundary curvature is proposed.
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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