93 citations · 476 across the 42 of their papers we have counts for
10 papers · 1 filter
Masked Video Distillation: Rethinking Masked Feature Modeling for Self-supervised Video Representation Learning
Rui Wang, Dongdong Chen, Zuxuan Wu +5
Benefiting from masked visual modeling, self-supervised video representation learning has achieved remarkable progress. However, existing methods focus on learning representations…
Self-Supervised Learning based on Heat Equation
Yinpeng Chen, Xiyang Dai, Dongdong Chen +4
This paper presents a new perspective of self-supervised learning based on extending heat equation into high dimensional feature space. In particular, we remove time dependence by…
Video Mobile-Former: Video Recognition with Efficient Global Spatial-temporal Modeling
Rui Wang, Zuxuan Wu, Dongdong Chen +6
Transformer-based models have achieved top performance on major video recognition benchmarks. Benefiting from the self-attention mechanism, these models show stronger ability of mo…
Design What You Desire: Icon Generation from Orthogonal Application and Theme Labels
Yinpeng Chen, Zhiyu Pan, Min Shi +3
Generative adversarial networks (GANs) have been trained to be professional artists able to create stunning artworks such as face generation and image style transfer. In this paper…
Should All Proposals be Treated Equally in Object Detection?
Yunsheng Li, Yinpeng Chen, Xiyang Dai +7
The complexity-precision trade-off of an object detector is a critical problem for resource constrained vision tasks. Previous works have emphasized detectors implemented with effi…
Detection Hub: Unifying Object Detection Datasets via Query Adaptation on Language Embedding
Lingchen Meng, Xiyang Dai, Yinpeng Chen +7
Combining multiple datasets enables performance boost on many computer vision tasks. But similar trend has not been witnessed in object detection when combining multiple datasets d…
Reduce Information Loss in Transformers for Pluralistic Image Inpainting
Qiankun Liu, Zhentao Tan, Dongdong Chen +6
Transformers have achieved great success in pluralistic image inpainting recently. However, we find existing transformer based solutions regard each pixel as a token, thus suffer f…
Residual Mixture of Experts
Lemeng Wu, Mengchen Liu, Yinpeng Chen +3
Mixture of Experts (MoE) is able to scale up vision transformers effectively. However, it requires prohibiting computation resources to train a large MoE transformer. In this paper…
The Overlooked Classifier in Human-Object Interaction Recognition
Ying Jin, Yinpeng Chen, Lijuan Wang +5
Human-Object Interaction (HOI) recognition is challenging due to two factors: (1) significant imbalance across classes and (2) requiring multiple labels per image. This paper shows…
Extremely Weak Supervision Inversion of Multi-physical Properties
Shihang Feng, Peng Jin, Xitong Zhang +4
Multi-physical inversion plays a critical role in geophysics. It has been widely used to infer various physical properties~(such as velocity and conductivity). Among those inversio…