Zhenjun Zhao

Zhenjun Zhao

@ericzzj.bsky.social

ericzzj1989.github.io Postdoc@UniZar | PhD@CUHK | 3D vision, SLAM, Image matching (http://github.com/ericzzj1989/Awesome-Global-Solvers-for-3D-Vision)

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WovenAnchor Matcher: Specialized Intra- and Inter-Image Context Modeling for Feature Matching Zhiyang Li, Ruijiang Jin, Thibaut Klenke, Yusuke Sekikawa, Nakamasa Inoue tl;dr: separate intra-image and inter-image aggregation into two proposed modules arxiv.org/abs/2610.30799

Stream4D: Streaming 4D Reconstruction with Training-free Motion Decoupling via Causal KV-Cache Attention Wei Zhang, Ying Feng, Mengtong Wu, Shiqiang Gong, Huaqi Zhang, Qi Zhang tl;dr: causal attention encodes rich temporal motion cues within KV cache arxiv.org/abs/2610.31320

DLOSAC: Joint Spatial-Geometric Image Estimation via Delaunay-Guided Local Optimization RANSAC Yu Liu, Meiqi Zhou, Zipei Fan, Guanyuan Feng, Xuan Song tl;dr: candidate inliers->Delaunay triangulation->spatial distribution and geometric consistency losses->weighting->WLS arxiv.org/abs/2610.21215

Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation Sheng Ye, Jiangke Lin, Fudong Wang, Yi Yuan, Zhen-Hui Dong, Yong-Jin Liu tl;dr: replace the pixel-aligned paradigm with a compact anchor-based representation arxiv.org/abs/2610.21634

LonGaussian: Tracking Foundation Priors for Long-Context Feedforward Gaussian Reconstruction Zhoufeng Xie, Guanjun Wu, Shuai Zhang, Xinggang Wang, Wenyu Liu tl;dr: LoGeR’s chunk-wise hybrid memory + track-guided consolidation + artifact filtering arxiv.org/abs/2610.23250

Causal Spatiotemporal State Evolution for Monocular 4D Reconstruction Qiaowei Miao, Yijing Guo, Lipei Zhang, Qifeng Cheng, Yuru Xiao, Ziqian Ni, Sheng Yang tl;dr: directionally ordered spatiotemporal state evolution->monocular 4D visual geometry arxiv.org/abs/2610.27594

BlazeVGGT: 13x Faster VGGT at 2,000 Frames via Camera Token without Training Shujun Yao, Junhui Lin, Congying Han, Tiande Guo, Ziwen Liu, Bonan Li tl;dr: use evolving camera-token relations to select complementary views for KV sparsification arxiv.org/abs/2610.29454

tl;dr: learn compact ego-motion-conditioned registers during V-JEPA pretraining as a shared state interface for world modeling and planning

InfiniSplat v2: Analyzing and Improving Feed-Forward 3DGS from Any Views Yongzhen Hu, Hao Yu, Jiawei Wang, Xianming Zeng, Jianyun Xu, Xingliang Liu, Ruizhen Hu, Xiaowei Zhou, Hujun Bao, Sida Peng tl;dr: freeze geometry&learn Gaussian attributes arxiv.org/abs/2610.20341

BAT3R: Robust Online 3D Reconstruction with Bayesian Adaptive State Updates Lijian Li, Yuanpeng He, Yudian Zheng, Chung-ju Huang, Linyu Li, Dongming Jin, Wenpin Jiao, Zhi Jin, Chi-Man Pun tl;dr: Bayesian adaptation for uncertainty-aware state updating arxiv.org/abs/2610.16330

Towards Complementary Keypoint Detection via Mixture of Detectors Xiaoyong Lu, Guobao Xiao, Dong Liang, Songlin Du tl;dr: distill six detectors into multiple heads->router with reward-guided supervision selects most suitable detectors arxiv.org/abs/2610.16762

UniMetric: Universal Metric Scale Recovery for Visual Geometry Foundation Models Lei Yang, Yuner Zhang, Ziyang Liu, Ziying Song, Kai WU, Yiyang Gao, Jiangtao Su, Yiming Li tl;dr: uncertain object-size priors from VLM + GFM reconstruction->scale arxiv.org/abs/2610.16945

FLoTS-SLAM: Optical Flow-Derived Uncertainty for Monocular Dynamic SLAM with Two-Stage Optimization Haorui Du, Lipu Zhou tl;dr: optical flow and camera motion induced flow->residual->uncertainty; depth fix & poses est.->joint refinement of poses and depth arxiv.org/abs/2610.23496

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📊 Results on TUM RGB-D, 7-Scenes, Replica and KITTI 🔹 Best uncalibrated average ATE on TUM RGB-D (0.027 m) and Replica (0.002 m) 🔹 Well ahead of uncalibrated foundation-model SLAM baselines on KITTI 🔹 7-Scenes completion 0.030 → 0.015 m vs SLAM-Former 🔹 7.4 FPS on one A100 4/5

🤔 The idea Feed-forward geometry should enter SLAM as optimization-native measurements, not as a separate state One state (poses, inverse depths, intrinsics). Every edge stores a dense target coordinate and a confidence per pixel No second map. No after-the-fact state fusion 2/5

⏱️ Two clocks, one factor graph 🔹 DROID-Net handles local tracking 🔹 DINO + Flow3r sees a wider window and only refreshes existing edges 🛡️ A state-consistency gate accepts a refresh only if it agrees with the current geometry Without it, Replica ATE jumps from 0.0023 to 0.5848 m 3/5

Graph3R: Unifying View Graph Initialization with Feed-Forward Reconstruction Jingwen Yu, Hengli Wang, Jianhao Jiao, Zhonghang Liu, Ping Tan, Hong Zhang tl;dr: π3->verification head->pairwise covisibility->view graph->graph-conditioned reconstruction arxiv.org/abs/2610.16272

Physical SLAM: Physics-aware Simultaneous Localisation and Mapping Guangming Wang, Zhishuo Liu, Haibing Wu, Wanli Ma, Yixiong Jing, Olaf Wysocki, Brian Sheil tl;dr: dynamic object Gaussian field driven by spring-mass physical model arxiv.org/abs/2610.17260

CF-Splat: Closed-Form Triangle Splatting with Mesh Priors Yixin Fang, Liang Zhao tl;dr: mesh geometry&calibrated cameras->rendered pixel colors are linear with respect to per-vertex SH coefficients->multi-view appearance estimation->global LLS problem arxiv.org/abs/2610.22108

Efficient Confidence-Aware Densification for 3DGS Manuel Hofer, Thomas Köhler, Felix Windisch, Bernhard Kerbl, Markus Steinberger, Lukas Radl tl;dr: large screen-space gradients->new primitives->weighted learned confidence->relocate->contribute least arxiv.org/abs/2610.13541