35 citations · 147 across the 22 of their papers we have counts for
8 papers · 1 filter
A Close Look at Spatial Modeling: From Attention to Convolution
Xu Ma, Huan Wang, Can Qin +4
Vision Transformers have shown great promise recently for many vision tasks due to the insightful architecture design and attention mechanism. By revisiting the self-attention resp…
Real-Time Neural Light Field on Mobile Devices
Junli Cao, Huan Wang, Pavlo Chemerys +6
Recent efforts in Neural Rendering Fields (NeRF) have shown impressive results on novel view synthesis by utilizing implicit neural representation to represent 3D scenes. Due to th…
Look More but Care Less in Video Recognition
Yitian Zhang, Yue Bai, Huan Wang +2
Existing action recognition methods typically sample a few frames to represent each video to avoid the enormous computation, which often limits the recognition performance. To tack…
Parameter-Efficient Masking Networks
Yue Bai, Huan Wang, Xu Ma +3
A deeper network structure generally handles more complicated non-linearity and performs more competitively. Nowadays, advanced network designs often contain a large number of repe…
Trainability Preserving Neural Pruning
Huan Wang, Yun Fu
Many recent works have shown trainability plays a central role in neural network pruning -- unattended broken trainability can lead to severe under-performance and unintentionally…
Dual Lottery Ticket Hypothesis
Yue Bai, Huan Wang, Zhiqiang Tao +2
Fully exploiting the learning capacity of neural networks requires overparameterized dense networks. On the other side, directly training sparse neural networks typically results i…
R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis
Huan Wang, Jian Ren, Zeng Huang +4
Recent research explosion on Neural Radiance Field (NeRF) shows the encouraging potential to represent complex scenes with neural networks. One major drawback of NeRF is its prohib…
Hybrid Pixel-Unshuffled Network for Lightweight Image Super-Resolution
Bin Sun, Yulun Zhang, Songyao Jiang +1
Convolutional neural network (CNN) has achieved great success on image super-resolution (SR). However, most deep CNN-based SR models take massive computations to obtain high perfor…