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20232026
most citedPointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer

35 citations · 51 across the 23 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

CultureVidBench: Benchmarking Cultural Understanding in Text-to-Video Generation

Xianjing Han, Yuhan Su, Yang Deng +3

Text-to-video (T2V) generation models have advanced rapidly, yet their ability to represent diverse cultural contexts remains underexplored. Existing benchmarks mainly focus on per…

cs.CV2025

Modulo Video Recovery via Selective Spatiotemporal Vision Transformer

Tianyu Geng, Feng Ji, Wee Peng Tay

Conventional image sensors have limited dynamic range, causing saturation in high-dynamic-range (HDR) scenes. Modulo cameras address this by folding incident irradiance into a boun…

cs.CV2024

PRFusion: Toward Effective and Robust Multi-Modal Place Recognition with Image and Point Cloud Fusion

Sijie Wang, Qiyu Kang, Rui She +3

Place recognition plays a crucial role in the fields of robotics and computer vision, finding applications in areas such as autonomous driving, mapping, and localization. Place rec…

cs.CV202435 cited

PointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer

Rui She, Qiyu Kang, Sijie Wang +7

Point cloud registration is a fundamental technique in 3-D computer vision with applications in graphics, autonomous driving, and robotics. However, registration tasks under challe…

cs.CV20247 cited

PosDiffNet: Positional Neural Diffusion for Point Cloud Registration in a Large Field of View with Perturbations

Rui She, Sijie Wang, Qiyu Kang +5

Point cloud registration is a crucial technique in 3D computer vision with a wide range of applications. However, this task can be challenging, particularly in large fields of view…

cs.CV2023

DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition

Sijie Wang, Rui She, Qiyu Kang +4

The utilization of multi-modal sensor data in visual place recognition (VPR) has demonstrated enhanced performance compared to single-modal counterparts. Nonetheless, integrating a…