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20182023
most citedWhat Makes Convolutional Models Great on Long Sequence Modeling?

20 citations · 39 across the 8 of their papers we have counts for

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10 papers · 1 filter

cs.CV20232 cited

3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation

Yi Zhang, Pengliang Ji, Angtian Wang +3

Regression-based methods for 3D human pose estimation directly predict the 3D pose parameters from a 2D image using deep networks. While achieving state-of-the-art performance on s…

cs.CV20231 cited

Cross-Modal Concept Learning and Inference for Vision-Language Models

Yi Zhang, Ce Zhang, Yushun Tang +1

Large-scale pre-trained Vision-Language Models (VLMs), such as CLIP, establish the correlation between texts and images, achieving remarkable success on various downstream tasks wi…

cs.CV20231 cited

From Association to Generation: Text-only Captioning by Unsupervised Cross-modal Mapping

Junyang Wang, Ming Yan, Yi Zhang +1

With the development of Vision-Language Pre-training Models (VLPMs) represented by CLIP and ALIGN, significant breakthroughs have been achieved for association-based visual tasks s…

cs.CV2021

Nuisance-Label Supervision: Robustness Improvement by Free Labels

Xinyue Wei, Weichao Qiu, Yi Zhang +2

In this paper, we present a Nuisance-label Supervision (NLS) module, which can make models more robust to nuisance factor variations. Nuisance factors are those irrelevant to a tas…

cs.CV20216 cited

Dizygotic Conditional Variational AutoEncoder for Multi-Modal and Partial Modality Absent Few-Shot Learning

Yi Zhang, Sheng Huang, Xi Peng +1

Data augmentation is a powerful technique for improving the performance of the few-shot classification task. It generates more samples as supplements, and then this task can be tra…

cs.CV2020

Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation

Yingda Xia, Yi Zhang, Fengze Liu +2

The ability to detect failures and anomalies are fundamental requirements for building reliable systems for computer vision applications, especially safety-critical applications of…