3 citations · 7 across the 8 of their papers we have counts for
6 papers · 1 filter
A training-free framework for high-fidelity appearance transfer via diffusion transformers
Shengrong Gu, Ye Wang, Song Wu +4
Diffusion Transformers (DiTs) excel at generation, but their global self-attention makes controllable, reference-image-based editing a distinct challenge. Unlike U-Nets, naively in…
FreeControl: Efficient, Training-Free Structural Control via One-Step Attention Extraction
Jiang Lin, Xinyu Chen, Song Wu +7
Controlling the spatial and semantic structure of diffusion-generated images remains a challenge. Existing methods like ControlNet rely on handcrafted condition maps and retraining…
E-Motion: Future Motion Simulation via Event Sequence Diffusion
Song Wu, Zhiyu Zhu, Junhui Hou +2
Forecasting a typical object's future motion is a critical task for interpreting and interacting with dynamic environments in computer vision. Event-based sensors, which could capt…
GFFE: G-buffer Free Frame Extrapolation for Low-latency Real-time Rendering
Songyin Wu, Deepak Vembar, Anton Sochenov +4
Real-time rendering has been embracing ever-demanding effects, such as ray tracing. However, rendering such effects in high resolution and high frame rate remains challenging. Fram…
Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow
Song Wu, Kaichao You, Weihua He +5
Video frame interpolation is a challenging task due to the ever-changing real-world scene. Previous methods often calculate the bi-directional optical flows and then predict the in…
Decoupling Features and Coordinates for Few-shot RGB Relocalization
Siyan Dong, Songyin Wu, Yixin Zhuang +3
Cross-scene model adaption is crucial for camera relocalization in real scenarios. It is often preferable that a pre-learned model can be fast adapted to a novel scene with as few…