6 citations · 14 across the 15 of their papers we have counts for
7 papers · 1 filter
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…