6 citations · 14 across the 15 of their papers we have counts for
17 papers
GLASS: Geometry-aware Local Alignment and Structure Synchronization Network for 2D-3D Registration
Zhixin Cheng, Jiacheng Deng, Xinjun Li +5
Image-to-point cloud registration methods typically follow a coarse-to-fine pipeline, extracting patch-level correspondences and refining them into dense pixel-to-point matches. Ho…
Zero-Shot Depth from Defocus
Yiming Zuo, Hongyu Wen, Venkat Subramanian +5
Depth from Defocus (DfD) is the task of estimating a dense metric depth map from a focus stack. Unlike previous works overfitting to a certain dataset, this paper focuses on the ch…
TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels
Jiahao Lu, Weitao Xiong, Jiacheng Deng +6
Monocular 3D tracking aims to capture the long-term motion of pixels in 3D space from a single monocular video and has witnessed rapid progress in recent years. However, we argue t…
Adaptive Agent Selection and Interaction Network for Image-to-point cloud Registration
Zhixin Cheng, Xiaotian Yin, Jiacheng Deng +5
Typical detection-free methods for image-to-point cloud registration leverage transformer-based architectures to aggregate cross-modal features and establish correspondences. Howev…
CA-I2P: Channel-Adaptive Registration Network with Global Optimal Selection
Zhixin Cheng, Jiacheng Deng, Xinjun Li +5
Detection-free methods typically follow a coarse-to-fine pipeline, extracting image and point cloud features for patch-level matching and refining dense pixel-to-point corresponden…
Relation3D: Enhancing Relation Modeling for Point Cloud Instance Segmentation
Jiahao Lu, Jiacheng Deng
3D instance segmentation aims to predict a set of object instances in a scene, representing them as binary foreground masks with corresponding semantic labels. Currently, transform…
Bridge 2D-3D: Uncertainty-aware Hierarchical Registration Network with Domain Alignment
Zhixin Cheng, Jiacheng Deng, Xinjun Li +2
The method for image-to-point cloud registration typically determines the rigid transformation using a coarse-to-fine pipeline. However, directly and uniformly matching image patch…
SAS: Segment Any 3D Scene with Integrated 2D Priors
Zhuoyuan Li, Jiahao Lu, Jiacheng Deng +4
The open vocabulary capability of 3D models is increasingly valued, as traditional methods with models trained with fixed categories fail to recognize unseen objects in complex dyn…
Beyond the Final Layer: Hierarchical Query Fusion Transformer with Agent-Interpolation Initialization for 3D Instance Segmentation
Jiahao Lu, Jiacheng Deng, Tianzhu Zhang
3D instance segmentation aims to predict a set of object instances in a scene and represent them as binary foreground masks with corresponding semantic labels. Currently, transform…
DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering
Jiahao Lu, Jiacheng Deng, Ruijie Zhu +4
Dynamic scenes rendering is an intriguing yet challenging problem. Although current methods based on NeRF have achieved satisfactory performance, they still can not reach real-time…
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting
Ruijie Zhu, Yanzhe Liang, Hanzhi Chang +5
Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Altho…
Plane2Depth: Hierarchical Adaptive Plane Guidance for Monocular Depth Estimation
Li Liu, Ruijie Zhu, Jiacheng Deng +3
Monocular depth estimation aims to infer a dense depth map from a single image, which is a fundamental and prevalent task in computer vision. Many previous works have shown impress…
Diff3DETR:Agent-based Diffusion Model for Semi-supervised 3D Object Detection
Jiacheng Deng, Jiahao Lu, Tianzhu Zhang
3D object detection is essential for understanding 3D scenes. Contemporary techniques often require extensive annotated training data, yet obtaining point-wise annotations for poin…
Pamba: Enhancing Global Interaction in Point Clouds via State Space Model
Zhuoyuan Li, Yubo Ai, Jiahao Lu +7
Transformers have demonstrated impressive results for 3D point cloud semantic segmentation. However, the quadratic complexity of transformer makes computation costs high, limiting…
Unsupervised Template-assisted Point Cloud Shape Correspondence Network
Jiacheng Deng, Jiahao Lu, Tianzhu Zhang
Unsupervised point cloud shape correspondence aims to establish point-wise correspondences between source and target point clouds. Existing methods obtain correspondences directly…
BSNet: Box-Supervised Simulation-assisted Mean Teacher for 3D Instance Segmentation
Jiahao Lu, Jiacheng Deng, Tianzhu Zhang
3D instance segmentation (3DIS) is a crucial task, but point-level annotations are tedious in fully supervised settings. Thus, using bounding boxes (bboxes) as annotations has show…
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenes
Ziyang Song, Ruijie Zhu, Chuxin Wang +3
Self-supervised monocular depth estimation holds significant importance in the fields of autonomous driving and robotics. However, existing methods are typically trained and tested…