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Sheng Li

5 papers hereh-index 426 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG2
  • cs.GR1
same name
  • Sheng Li — 13 papers, h 17
  • Sheng Li — 11 papers, h 18
  • Sheng Li — 9 papers, h 6
  • Sheng Li — 7 papers, h 20
  • Sheng Li — 6 papers, h 7
  • Sheng Li — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

5 papers

cs.GR2026

Accelerating 3D Gaussian Splatting using Tensor Cores

Sheng Li, Yang Sui, Yue Wu +4

3D Gaussian Splatting (3DGS) has become a leading technique for real-time neural rendering and 3D scene reconstruction, but its rendering cost remains too high for many latency-sen…

cs.CV2026

Temporal Aware Pruning for Efficient Diffusion-based Video Generation

Sheng Li, Yang Sui, Junhao Ran +3

Video diffusion models have recently enabled high-quality video generation with ViT-based architectures, but remain computationally intensive because generation requires attention…

cs.CV2026

DRNet: All-in-One Image Restoration via Prior-Guided Dynamic Reparameterization

Ao Li, Xiaoning Liu, Sheng Li +5

All-in-one image restoration aims to handle diverse degradations within a single model. However, existing methods often suffer from three key limitations: 1) per-input computationa…

cs.LG2025

Rethinking the Potential of Layer Freezing for Efficient DNN Training

Chence Yang, Ci Zhang, Lei Lu +11

With the growing size of deep neural networks and datasets, the computational costs of training have significantly increased. The layer-freezing technique has recently attracted gr…

cs.LG2025

EdgeOL: Efficient in-situ Online Learning on Edge Devices

Sheng Li, Geng Yuan, Yue Dai +10

Emerging applications, such as robot-assisted eldercare and object recognition, generally employ deep learning neural networks (DNNs) and naturally require: i) handling streaming-i…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.