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Shuwei Shi

7 accepted papers

2025

Mimir: Improving Video Diffusion Models for Precise Text Understanding

CVPR 2025poster

Text serves as the key control signal in video generation due to its narrative nature. To render text descriptions into video clips, current video diffusion models borrow features from text encoders yet struggle with limited text comprehension. The recent success of large language models (LLMs) show…

Cited by 4SourcePDFScholar
2025

MotionStone: Decoupled Motion Intensity Modulation with Diffusion Transformer for Image-to-Video Generation

CVPR 2025poster

The image-to-video (I2V) generation is conditioned on the static image, which has been enhanced recently by the motion intensity as an additional control signal. These motion-aware models are appealing to generate diverse motion patterns, yet there lacks a reliable motion estimator for training such…

Cited by 4SourcePDFScholar
2025

ResMaster: Mastering High-Resolution Image Generation via Structural and Fine-Grained Guidance

AAAI 2025technical

Diffusion models excel at producing high-quality images; however, scaling to higher resolutions, such as 4K, often results in structural distortions, and repetitive patterns. To this end, we introduce ResMaster, a novel, training-free method that empowers resolution-limited diffusion models to gener…

Cited by 11SourcePDFScholar
2023

Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment

NeurIPS 2023poster

Blind Omnidirectional Image Quality Assessment (BOIQA) aims to objectively assess the human perceptual quality of omnidirectional images (ODIs) without relying on pristine-quality image information. It is becoming more significant with the increasing advancement of virtual reality (VR) technology. H…

2023

Mitigating Artifacts in Real-World Video Super-resolution Models

AAAI 2023technical

The recurrent structure is a prevalent framework for the task of video super-resolution, which models the temporal dependency between frames via hidden states. When applied to real-world scenarios with unknown and complex degradations, hidden states tend to contain unpleasant artifacts and propagate…

2022

Attention Probe: Vision Transformer Distillation in the Wild

ICASSP 2022accepted

Vision transformers (ViTs) require intensive computational resources to achieve high performance, which usually makes them not suitable for mobile devices. A feasible strategy is to compress them using the original training data, which may be not accessible due to privacy limitations or transmission…

Cited by 0SourceScholar
2022

Rethinking Alignment in Video Super-Resolution Transformers

NeurIPS 2022accept

The alignment of adjacent frames is considered an essential operation in video super-resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are generally equipped with well-designed alignment modules. However, the progress of the self-attention mechanism may violate this commo…