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20222026
most citedGait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline

1 citations · 1 across the 5 of their papers we have counts for

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cs.CV2026

PolarScale: A Physics-Grounded Benchmark for Radiometrically Consistent RGB-to-Stokes Estimation

Beibei Lin, Tingting Chen, Xin Zhang +3

Polarization imaging provides physical cues beyond intensity imaging but typically requires specialized hardware. Recent methods infer polarization from RGB-like inputs, yet predic…

cs.CV2026

WeatherReasonSeg: A Benchmark for Weather-Aware Reasoning Segmentation in Visual Language Models

Wanjun Du, Zifeng Yuan, Tingting Chen +3

Existing vision-language models (VLMs) have demonstrated impressive performance in reasoning-based segmentation. However, current benchmarks are primarily constructed from high-qua…

cs.CV2025

GeoComplete: Geometry-Aware Diffusion for Reference-Driven Image Completion

Beibei Lin, Tingting Chen, Robby T. Tan

Reference-driven image completion, which restores missing regions in a target view using additional images, is particularly challenging when the target view differs significantly f…

cs.CV2025

OmniRaindrop: A Comprehensive Benchmark for Dual-Focused Raindrop Removal under Day and Night Scenes

Zhiqiang Teng, Tingting Chen, Beibei Lin +4

Adherent raindrops on camera lenses are a pervasive source of real-world image degradation, undermining outdoor visual perception for downstream applications such as robotics and 3…

cs.CV2025

RGB-to-Polarization Estimation: A New Task and Benchmark Study

Beibei Lin, Zifeng Yuan, Tingting Chen

Polarization images provide rich physical information that is fundamentally absent from standard RGB images, benefiting a wide range of computer vision applications such as reflect…

cs.CV2022★ 1 cited

Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline

Xianda Guo, Zheng Zhu, Tian Yang +6

Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognit…