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20212024
most citedUni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs

28 citations · 72 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024★ 14 cited

Power-LLaVA: Large Language and Vision Assistant for Power Transmission Line Inspection

Jiahao Wang, Mingxuan Li, Haichen Luo +4

The inspection of power transmission line has achieved notable achievements in the past few years, primarily due to the integration of deep learning technology. However, current in…

cs.CV2024★ 1 cited

Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning

Chenyu Yang, Xizhou Zhu, Jinguo Zhu +9

Recently, vision model pre-training has evolved from relying on manually annotated datasets to leveraging large-scale, web-crawled image-text data. Despite these advances, there is…

cs.CV2022★ 3 cited

Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks

Hao Li, Jinguo Zhu, Xiaohu Jiang +8

Despite the remarkable success of foundation models, their task-specific fine-tuning paradigm makes them inconsistent with the goal of general perception modeling. The key to elimi…

cs.CV2022★ 28 cited

Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs

Jinguo Zhu, Xizhou Zhu, Wenhai Wang +4

To build an artificial neural network like the biological intelligence system, recent works have unified numerous tasks into a generalist model, which can process various tasks wit…

cs.CV2021★ 8 cited

Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks

Xizhou Zhu, Jinguo Zhu, Hao Li +5

Biological intelligence systems of animals perceive the world by integrating information in different modalities and processing simultaneously for various tasks. In contrast, curre…

cs.CV2021★ 4 cited

Layerwise Optimization by Gradient Decomposition for Continual Learning

Shixiang Tang, Dapeng Chen, Jinguo Zhu +2

Deep neural networks achieve state-of-the-art and sometimes super-human performance across various domains. However, when learning tasks sequentially, the networks easily forget th…

cs.CV2021★ 13 cited

Multiple Domain Experts Collaborative Learning: Multi-Source Domain Generalization For Person Re-Identification

Shijie Yu, Feng Zhu, Dapeng Chen +5

Recent years have witnessed significant progress in person re-identification (ReID). However, current ReID approaches still suffer from considerable performance degradation when un…

cs.CV2021★ 1 cited

Complementary Relation Contrastive Distillation

Jinguo Zhu, Shixiang Tang, Dapeng Chen +5

Knowledge distillation aims to transfer representation ability from a teacher model to a student model. Previous approaches focus on either individual representation distillation o…