90 citations · 97 across the 5 of their papers we have counts for
5 papers
A Pixel Is Worth More Than One 3D Gaussians in Single-View 3D Reconstruction
Jianghao Shen, Nan Xue, Tianfu Wu
Learning 3D scene representation from a single-view image is a long-standing fundamental problem in computer vision, with the inherent ambiguity in predicting contents unseen from…
Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image Recognition
Jianghao Shen, Tianfu Wu
Learning light-weight yet expressive deep networks in both image synthesis and image recognition remains a challenging problem. Inspired by a more recent observation that it is the…
Growing Deep Forests Efficiently with Soft Routing and Learned Connectivity
Jianghao Shen, Sicheng Wang, Zhangyang Wang
Despite the latest prevailing success of deep neural networks (DNNs), several concerns have been raised against their usage, including the lack of intepretability the gap between D…
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference
Jianghao Shen, Yonggan Fu, Yue Wang +3
While increasingly deep networks are still in general desired for achieving state-of-the-art performance, for many specific inputs a simpler network might already suffice. Existing…
Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference
Yue Wang, Jianghao Shen, Ting-Kuei Hu +5
State-of-the-art convolutional neural networks (CNNs) yield record-breaking predictive performance, yet at the cost of high-energy-consumption inference, that prohibits their widel…