Shanchuan Lin

According to our database1, Shanchuan Lin authored at least 19 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Adversarial Distribution Matching for Diffusion Distillation Towards Efficient Image and Video Synthesis.
CoRR, July, 2025

VINCIE: Unlocking In-context Image Editing from Video.
CoRR, June, 2025

Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generation.
CoRR, June, 2025

Seedance 1.0: Exploring the Boundaries of Video Generation Models.
CoRR, June, 2025

SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training.
CoRR, June, 2025

Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model.
CoRR, April, 2025

Training-free Diffusion Acceleration with Bottleneck Sampling.
CoRR, March, 2025

CameraCtrl II: Dynamic Scene Exploration via Camera-controlled Video Diffusion Models.
CoRR, March, 2025

Diffusion Adversarial Post-Training for One-Step Video Generation.
CoRR, January, 2025

2024
Is Your Text-to-Image Model Robust to Caption Noise?
CoRR, 2024

AnimateDiff-Lightning: Cross-Model Diffusion Distillation.
CoRR, 2024

SDXL-Lightning: Progressive Adversarial Diffusion Distillation.
CoRR, 2024

Diffusion Model with Perceptual Loss.
CoRR, 2024

Common Diffusion Noise Schedules and Sample Steps are Flawed.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
MagicProp: Diffusion-based Video Editing via Motion-aware Appearance Propagation.
CoRR, 2023

2022
Robust High-Resolution Video Matting with Temporal Guidance.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

2021
Real-Time High-Resolution Background Matting.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Fact or Fiction: Verifying Scientific Claims.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019


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