← Search

Lijing Lu

4 accepted papers

2026

Confidence-Guided Multi-Scale Aggregation for Sparse-View High-Resolution 3D Gaussian Splatting

CVPR 2026

Sparse-view 3D Gaussian Splatting (3DGS) reconstructs scenes using 3D Gaussians from sparse input views. Yet, this method is prone to overfitting, which is exacerbated at higher resolutions as the expanded dimensionality amplifies floating artifacts and reconstruction ambiguities. In this paper, we

Cited by 0SourceScholar
2026

One-to-All Animation: Alignment-Free Character Animation and Image Pose Transfer

CVPR 2026

Recent advances in diffusion models have greatly improved pose-driven character animation. However, existing methods are limited to spatially aligned reference-pose pairs with matched skeletal structures. Handling reference-pose misalignment remains unsolved. To address this, we present One-to-All A

Cited by 0SourcecodeScholar
2025

Diffusion-based Synthetic Data Generation for Visible-Infrared Person Re-Identification

AAAI 2025technical

The performance of models is intricately linked to the abundance of training data. In Visible-Infrared person Re-IDentification (VI-ReID) tasks, collecting and annotating large-scale images of each individual under various cameras and modalities is tedious, time-expensive, costly and must comply wit…

Cited by 0SourcePDFScholar
2025

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution

CVPR 2025poster

Existing diffusion-based video super-resolution (VSR) methods are susceptible to introducing complex degradations and noticeable artifacts into high-resolution videos due to their inherent randomness. In this paper, we propose a noise-robust real-world VSR framework by incorporating self-supervised…

Cited by 0SourcePDFScholar