4 citations · 8 across the 8 of their papers we have counts for
9 papers · 1 filter
Twins: Learn to Predict Unified Representations with Focal Loss
Kaixiong Gong, Xin Cai, Bin Lin +9
Unified multimodal models seek a shared visual token space that supports both multimodal understanding and image generation. Discrete methods unify the interface via a shared codeb…
GEAR: Guided End-to-End AutoRegression for Image Synthesis
Bin Lin, Zheyuan Liu, Chenguo Lin +8
Visual generative models are typically trained in two stages. A tokenizer is first trained for reconstruction and then frozen, after which a generator is trained on its discrete in…
Manifold-Aware Exploration for Reinforcement Learning in Video Generation
Mingzhe Zheng, Weijie Kong, Yue Wu +9
Group Relative Policy Optimization (GRPO) methods for video generation like FlowGRPO remain far less reliable than their counterparts for language models and images. This gap arise…
FlashI2V: Fourier-Guided Latent Shifting Prevents Conditional Image Leakage in Image-to-Video Generation
Yunyang Ge, Xinhua Cheng, Chengshu Zhao +5
In Image-to-Video (I2V) generation, a video is created using an input image as the first-frame condition. Existing I2V methods concatenate the full information of the conditional i…
SwapAnyone: Consistent and Realistic Video Synthesis for Swapping Any Person into Any Video
Chengshu Zhao, Yunyang Ge, Xinhua Cheng +6
Video body-swapping aims to replace the body in an existing video with a new body from arbitrary sources, which has garnered more attention in recent years. Existing methods treat…
WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
Yuwei Niu, Munan Ning, Mengren Zheng +9
Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evaluation standards predominantly focus on…
Next Patch Prediction for Autoregressive Visual Generation
Yatian Pang, Peng Jin, Shuo Yang +8
Autoregressive models, built based on the Next Token Prediction (NTP) paradigm, show great potential in developing a unified framework that integrates both language and vision task…
DreamDance: Animating Human Images by Enriching 3D Geometry Cues from 2D Poses
Yatian Pang, Bin Zhu, Bin Lin +5
In this work, we present DreamDance, a novel method for animating human images using only skeleton pose sequences as conditional inputs. Existing approaches struggle with generatin…
Interactive Character Control with Auto-Regressive Motion Diffusion Models
Yi Shi, Jingbo Wang, Xuekun Jiang +3
Real-time character control is an essential component for interactive experiences, with a broad range of applications, including physics simulations, video games, and virtual reali…