9 citations · 10 across the 4 of their papers we have counts for
5 papers
Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
Zibo Zhao, Zeqiang Lai, Qingxiang Lin +71
We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two foundation components: a large-sca…
Learn to See Faster: Pushing the Limits of High-Speed Camera with Deep Underexposed Image Denoising
Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima +1
The ability to record high-fidelity videos at high acquisition rates is central to the study of fast moving phenomena. The difficulty of imaging fast moving scenes lies in a trade-…
Optical Flow Regularization of Implicit Neural Representations for Video Frame Interpolation
Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima +1
Recent works have shown the ability of Implicit Neural Representations (INR) to carry meaningful representations of signal derivatives. In this work, we leverage this property to p…
Memory-Efficient CNN Accelerator Based on Interlayer Feature Map Compression
Zhuang Shao, Xiaoliang Chen, Li Du +6
Existing deep convolutional neural networks (CNNs) generate massive interlayer feature data during network inference. To maintain real-time processing in embedded systems, large on…
Reversible designs for extreme memory cost reduction of CNN training
Tristan Hascoet, Quentin Febvre, Yasuo Ariki +1
Training Convolutional Neural Networks (CNN) is a resource intensive task that requires specialized hardware for efficient computation. One of the most limiting bottleneck of CNN t…