80 citations · 92 across the 3 of their papers we have counts for
3 papers
cs.CV2024
LN3DIFF++: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation
Yushi Lan, Fangzhou Hong, Shangchen Zhou +7
The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved su…
cs.CV2018★ 12 cited
An Embarrassingly Simple Approach for Knowledge Distillation
Mengya Gao, Yujun Shen, Quanquan Li +5
Knowledge Distillation (KD) aims at improving the performance of a low-capacity student model by inheriting knowledge from a high-capacity teacher model. Previous KD methods typica…
cs.CV2018★ 80 cited
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation
Tak-Wai Hui, Xiaoou Tang, Chen Change Loy
FlowNet2, the state-of-the-art convolutional neural network (CNN) for optical flow estimation, requires over 160M parameters to achieve accurate flow estimation. In this paper we p…