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20212023
most citedFew-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning

15 citations · 64 across the 22 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023

Memory-and-Anticipation Transformer for Online Action Understanding

Jiahao Wang, Guo Chen, Yifei Huang +2

Most existing forecasting systems are memory-based methods, which attempt to mimic human forecasting ability by employing various memory mechanisms and have progressed in temporal…

cs.CV2023★ 1 cited

Generating Images with 3D Annotations Using Diffusion Models

Wufei Ma, Qihao Liu, Jiahao Wang +11

Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack e…

cs.CV2023★ 15 cited

VideoLLM: Modeling Video Sequence with Large Language Models

Guo Chen, Yin-Dong Zheng, Jiahao Wang +8

With the exponential growth of video data, there is an urgent need for automated technology to analyze and comprehend video content. However, existing video understanding models ar…

cs.CV2023

RIFormer: Keep Your Vision Backbone Effective While Removing Token Mixer

Jiahao Wang, Songyang Zhang, Yong Liu +6

This paper studies how to keep a vision backbone effective while removing token mixers in its basic building blocks. Token mixers, as self-attention for vision transformers (ViTs),…

cs.CV2023

OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

Bingchen Zhao, Jiahao Wang, Wufei Ma +7

Enhancing the robustness of vision algorithms in real-world scenarios is challenging. One reason is that existing robustness benchmarks are limited, as they either rely on syntheti…

cs.LG2023★ 1 cited

Edge-free but Structure-aware: Prototype-Guided Knowledge Distillation from GNNs to MLPs

Taiqiang Wu, Zhe Zhao, Jiahao Wang +4

Distilling high-accuracy Graph Neural Networks (GNNs) to low-latency multilayer perceptions (MLPs) on graph tasks has become a hot research topic. However, conventional MLP learnin…