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Canada-0-LABORATORIES företaget Kataloger
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Företag Nyheter:
- Wenhao Wu (吴文灏)
Wenhao Wu is an Applied Scientist at Amazon AGI working on the Amazon Foundation Model: Nova Before joining Amazon, he spent nearly seven years (2018-2025) at Baidu VIS working with Chief Scientist Dr Jingdong Wang (IEEE Fellow) There, he progressed from a research intern into a Senior Staff Researcher and contributed to multiple large-scale computer vision and multimodal projects He
- WENHAO WU (吴吴吴
Wenhao Wu, Huanjin Yao, Mengxi Zhang, Yuxin Song, Wanli Ouyang, Jingdong Wang ¥Stars 187+ Technical Report, ArXiv:2311 15732
- Publications - GitHub Pages
Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, Yi Yang, Shilei Wen CVPR 2020 Workshop on Efficient Deep Learning in Computer Vision Oral [ PDF ] [ Slides ] Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, Shilei Wen
- CVPR20_EDLCV_Oral_15min - GitHub Pages
Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, and Shilei Wen Multi-agent reinforcement learning based frame sampling for effective untrimmed video recognition
- DSANet: Dynamic Segment Aggregation Network for Video-Level . . .
Task Video Recognition: classify the short clip or untrimmed video into pre-defined class
- MVFNet: Multi-View Fusion Network for Efficient Video Recognition
MVFNet: Multi-View Fusion Network for Efficient Video Recognition Wenhao Wu1, Dongliang He1, Tianwei Lin1, Fu Li1, Chuang Gan2, Errui Ding1
- Revisiting Classifier:Transferring Vision-Language Models for Video . . .
Key Observations: Revisiting Classifier Figure Inter-class correlation maps of “embeddings of class labels” for 20 categories on Kinetics-400 Left: The extracted textual vectors of class labels, Right: The “embeddings” from learned classifier 3 Our efficient vision-language transferring framework
- Appearance-SpeedConsistency ASCNet: Self . . .
App earance-Sp eed Consistency Deng Huangy , Wenhao Wuy , Weiwen Hu, Xu Liu, Dongliang He, Zhihua Wu, Xiangmiao Wu, Mingkui Tan and Errui Ding
- ICCV19_Oral_5min - whwu95. github. io
Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition Wenhao Wu Dongliang He Xiao Tan Shifeng Chen Shilei Wen
- Multi-Agent Reinforcement Learning Based Frame Sampling for Effective . . .
Ø We focus on a previously overlooked point, i e , the frame sampling strategy, in improving untrimmed video classification performance and intuitively formulate it as a Markov decision process Ø Multi-agent reinforcement learning is adopted to solve the formulated sequential decision problems A novel framework that takes both context information and historical environment states into
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