works on

From the 1 of 8 linked papers with an AI index.

activity
20242026
collaborators

8 papers

cs.CV2026

Robust Global Structure-from-Motion via View Graph Pruning

Jiamin Xu, Lixing Yao, Weichen Dai +4

Structure-from-Motion (SfM) aims to estimate camera poses and reconstruct 3D structures from a collection of unordered images. Compared with incremental SfM, global SfM achieves be…

cs.CV2026

WildShadowRemover: In-the-Wild Video Shadow Removal via Detail-Preserving Video Diffusion Models

Jiamin Xu, Cong Wang, Zheng Dong +4

The paper introduces WildShadowRemover, a system that fine‑tunes a pretrained video diffusion model to remove shadows from real‑world videos while preserving fine details and tempo…

cs.CV2026

Robust Activation Map Rectification for Weakly Supervised Volumetric Segmentation: Temporal Coherence as a Free Lunch

Renshu Gu, Jialiang Chen, Fei Gao +8

Weakly supervised segmentation relies heavily on class activation maps (CAMs) to initially localize target regions. However, CAMs are often noisy and prone to catastrophic failures…

cs.CL2026

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning

Run Zou, Jianhang Ding, Yifan Ding +3

Instruction tuning has optimized the specialized capabilities of large language models (LLMs), but it often requires extensive datasets and prolonged training times. The challenge…

cs.CV2025

OmniSR: Shadow Removal under Direct and Indirect Lighting

Jiamin Xu, Zelong Li, Yuxin Zheng +4

Shadows can originate from occlusions in both direct and indirect illumination. Although most current shadow removal research focuses on shadows caused by direct illumination, shad…

cs.CV2024

Detail-Preserving Latent Diffusion for Stable Shadow Removal

Jiamin Xu, Yuxin Zheng, Zelong Li +4

Achieving high-quality shadow removal with strong generalizability is challenging in scenes with complex global illumination. Due to the limited diversity in shadow removal dataset…