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20182025
most citedThe Efficiency Spectrum of Large Language Models: An Algorithmic Survey

11 citations · 37 across the 24 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

Motion Graph Unleashed: A Novel Approach to Video Prediction

Yiqi Zhong, Luming Liang, Bohan Tang +2

We introduce motion graph, a novel approach to the video prediction problem, which predicts future video frames from limited past data. The motion graph transforms patches of video…

cs.CV2024

OFER: Occluded Face Expression Reconstruction

Pratheba Selvaraju, Victoria Fernandez Abrevaya, Timo Bolkart +4

Reconstructing 3D face models from a single image is an inherently ill-posed problem, which becomes even more challenging in the presence of occlusions. In addition to fewer availa…

cs.LG2024

HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning

Tianyi Chen, Xiaoyi Qu, David Aponte +7

Structured pruning is one of the most popular approaches to effectively compress the heavy deep neural networks (DNNs) into compact sub-networks while retaining performance. The ex…

cs.CV2024★ 3 cited

FORA: Fast-Forward Caching in Diffusion Transformer Acceleration

Pratheba Selvaraju, Tianyu Ding, Tianyi Chen +2

Diffusion transformers (DiT) have become the de facto choice for generating high-quality images and videos, largely due to their scalability, which enables the construction of larg…

cs.CV2024

AdaContour: Adaptive Contour Descriptor with Hierarchical Representation

Tianyu Ding, Jinxin Zhou, Tianyi Chen +3

Existing angle-based contour descriptors suffer from lossy representation for non-starconvex shapes. By and large, this is the result of the shape being registered with a single gl…

cs.CV2024

S3Editor: A Sparse Semantic-Disentangled Self-Training Framework for Face Video Editing

Guangzhi Wang, Tianyi Chen, Kamran Ghasedi +6

Face attribute editing plays a pivotal role in various applications. However, existing methods encounter challenges in achieving high-quality results while preserving identity, edi…