activity
20232025
most citedLAMP: Learn A Motion Pattern for Few-Shot-Based Video Generation

10 citations · 10 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ML2025

Continuous Semi-Implicit Models

Longlin Yu, Jiajun Zha, Tong Yang +4

Semi-implicit distributions have shown great promise in variational inference and generative modeling. Hierarchical semi-implicit models, which stack multiple semi-implicit layers,…

cs.CV2025

Predicting 3D representations for Dynamic Scenes

Di Qi, Tong Yang, Beining Wang +2

We present a novel framework for dynamic radiance field prediction given monocular video streams. Unlike previous methods that primarily focus on predicting future frames, our meth…

stat.ML2024

Reflected Flow Matching

Tianyu Xie, Yu Zhu, Longlin Yu +5

Continuous normalizing flows (CNFs) learn an ordinary differential equation to transform prior samples into data. Flow matching (FM) has recently emerged as a simulation-free appro…

cs.CV2024

Slot-guided Volumetric Object Radiance Fields

Di Qi, Tong Yang, Xiangyu Zhang

We present a novel framework for 3D object-centric representation learning. Our approach effectively decomposes complex scenes into individual objects from a single image in an uns…

cs.LG2023

Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration

Longlin Yu, Tianyu Xie, Yu Zhu +3

Semi-implicit variational inference (SIVI) has been introduced to expand the analytical variational families by defining expressive semi-implicit distributions in a hierarchical ma…

cs.CV202310 cited

LAMP: Learn A Motion Pattern for Few-Shot-Based Video Generation

Ruiqi Wu, Liangyu Chen, Tong Yang +3

With the impressive progress in diffusion-based text-to-image generation, extending such powerful generative ability to text-to-video raises enormous attention. Existing methods ei…