3 citations · 6 across the 12 of their papers we have counts for
13 papers · 1 filter
GeoFlow: Efficient Driving Video Generation via Geometry-Aligned Priors
Jiazheng Liu, Hang Li, Jiawei Zhang +5
Generative models like Diffusion Models and Flow Matching have demonstrated remarkable capabilities in synthesizing high-fidelity driving videos, but are severely constrained by hi…
Learning Gaussian Structure: Intervention-Guided Density Control for Feed-Forward Driving Reconstruction
Hang Li, Jiahe Li, Meiying Gu +3
Feed-forward Gaussian reconstruction has recently emerged as an efficient approach for driving scene reconstruction. However, prevailing LiDAR-based methods preserve the initial co…
Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction
Jiahe Li, Jiawei Zhang, Xiao Bai +4
Surface reconstruction with differentiable rendering has achieved impressive performance in recent years, yet the pervasive photometric ambiguities have strictly bottlenecked exist…
SCE-SLAM: Scale-Consistent Monocular SLAM via Scene Coordinate Embeddings
Yuchen Wu, Jiahe Li, Xiaohan Yu +3
Monocular visual SLAM enables 3D reconstruction from internet video and autonomous navigation on resource-constrained platforms, yet suffers from scale drift, i.e., the gradual div…
FoundationSLAM: Unleashing the Power of Depth Foundation Models for End-to-End Dense Visual SLAM
Yuchen Wu, Jiahe Li, Fabio Tosi +3
We present FoundationSLAM, a learning-based monocular dense SLAM system that addresses the absence of geometric consistency in previous flow-based approaches for accurate and robus…
SparseSurf: Sparse-View 3D Gaussian Splatting for Surface Reconstruction
Meiying Gu, Jiawei Zhang, Jiahe Li +4
Recent advances in optimizing Gaussian Splatting for scene geometry have enabled efficient reconstruction of detailed surfaces from images. However, when input views are sparse, su…
GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction
Jiahe Li, Jiawei Zhang, Youmin Zhang +4
Reconstructing accurate surfaces with radiance fields has achieved remarkable progress in recent years. However, prevailing approaches, primarily based on Gaussian Splatting, are i…
InsTaG: Learning Personalized 3D Talking Head from Few-Second Video
Jiahe Li, Jiawei Zhang, Xiao Bai +3
Despite exhibiting impressive performance in synthesizing lifelike personalized 3D talking heads, prevailing methods based on radiance fields suffer from high demands for training…
Prompting Continual Person Search
Pengcheng Zhang, Xiaohan Yu, Xiao Bai +2
The development of person search techniques has been greatly promoted in recent years for its superior practicality and challenging goals. Despite their significant progress, exist…
CoR-GS: Sparse-View 3D Gaussian Splatting via Co-Regularization
Jiawei Zhang, Jiahe Li, Xiaohan Yu +4
3D Gaussian Splatting (3DGS) creates a radiance field consisting of 3D Gaussians to represent a scene. With sparse training views, 3DGS easily suffers from overfitting, negatively…
TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis via Gaussian Splatting
Jiahe Li, Jiawei Zhang, Xiao Bai +4
Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevaili…
DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization
Jiahe Li, Jiawei Zhang, Xiao Bai +4
Radiance fields have demonstrated impressive performance in synthesizing novel views from sparse input views, yet prevailing methods suffer from high training costs and slow infere…
Robust Synthetic-to-Real Transfer for Stereo Matching
Jiawei Zhang, Jiahe Li, Lei Huang +4
With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains. However, few studies have in…