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20192026
most citedDisentangled Representation Learning for 3D Face Shape

2 citations · 2 across the 5 of their papers we have counts for

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cs.CV2026

OVEarth-Bench: Evaluating Category Breadth and Query Diversity for Open-Vocabulary Earth Observation

Kaiyu Li, Zepeng Xin, Zixuan Jiang +4

Open-vocabulary Earth observation (EO) aims to localize geospatial concepts specified in natural language rather than a fixed label set. Existing benchmarks, however, usually cover…

cs.CV2026

The Second Challenge on Cross-Domain Few-Shot Object Detection at NTIRE 2026: Methods and Results

Xingyu Qiu, Yuqian Fu, Jiawei Geng +70

Cross-domain few-shot object detection (CD-FSOD) remains a challenging problem for existing object detectors and few-shot learning approaches, particularly when generalizing across…

cs.CV2025

DescribeEarth: Describe Anything for Remote Sensing Images

Kaiyu Li, Zixuan Jiang, Xiangyong Cao +4

Automated textual description of remote sensing images is crucial for unlocking their full potential in diverse applications, from environmental monitoring to urban planning and di…

cs.CV2025

Annotation-Free Open-Vocabulary Segmentation for Remote-Sensing Images

Kaiyu Li, Xiangyong Cao, Ruixun Liu +4

Semantic segmentation of remote sensing (RS) images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high exp…

cs.CV2019★ 2 cited

Disentangled Representation Learning for 3D Face Shape

Zi-Hang Jiang, Qianyi Wu, Keyu Chen +1

In this paper, we present a novel strategy to design disentangled 3D face shape representation. Specifically, a given 3D face shape is decomposed into identity part and expression…