84 citations · 126 across the 17 of their papers we have counts for
18 papers · 1 filter
Mask Forcing: Improving Autoregressive Video Diffusion Distillation via Dual-Noise Masking Rollout
Zhuoran Zhao, Shengju Qian, Tongtong Liang +7
Autoregressive (AR) video diffusion models have shown great potential in real-time video generation. Recent methods distill pretrained bidirectional video diffusion models into cau…
SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models
Junchao Huang, Guian Fang, Shengju Qian +15
We introduce SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference. Training across heterogeneous data s…
FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control
Songchun Zhang, Sitong Guo, Xianghao Kong +4
Generative video compositing, which involves inserting external assets seamlessly into existing video sequences, is essential for content creation and visual effects. However, exis…
MagicPrompt: Ultra-Lightweight Prompt Tuning for Video Generation
Yinhan Zhang, Dingwei Tan, Xianghao Kong +3
Large-scale video diffusion models deliver strong generation performance, but full fine-tuning for downstream tasks incurs prohibitive computational costs. Existing parameter-effic…
Video-MME-Logical: A Controlled Diagnostic Benchmark for Video Temporal-Logical Reasoning
Hohin Kwan, Hongyu Li, Ray Zhang +5
Recent interest in multimodal large language models (MLLMs) raises a central question: can they reason over dynamic visual evidence rather than merely recognize objects or events i…
UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors
Houyuan Chen, Hong Li, Xianghao Kong +8
Recent progress has shown that video diffusion models (VDMs) can be repurposed for diverse multimodal graphics tasks. However, existing methods often train separate models for each…
Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models
Songlin Yang, Xianghao Kong, Anyi Rao
Unified multimodal models (UMMs) were designed to combine the reasoning ability of large language models (LLMs) with the generation capability of vision models. In practice, howeve…
Astrolabe: Steering Forward-Process Reinforcement Learning for Distilled Autoregressive Video Models
Songchun Zhang, Zeyue Xue, Siming Fu +6
Distilled autoregressive (AR) video models enable efficient streaming generation but frequently misalign with human visual preferences. Existing reinforcement learning (RL) framewo…
ShotVerse: Advancing Cinematic Camera Control for Text-Driven Multi-Shot Video Creation
Songlin Yang, Zhe Wang, Xuyi Yang +7
Text-driven video generation has democratized film creation, but camera control in cinematic multi-shot scenarios remains a significant block. Implicit textual prompts lack precisi…
SesaHand: Enhancing 3D Hand Reconstruction via Controllable Generation with Semantic and Structural Alignment
Zhuoran Zhao, Xianghao Kong, Linlin Yang +3
Recent studies on 3D hand reconstruction have demonstrated the effectiveness of synthetic training data to improve estimation performance. However, most methods rely on game engine…
Composing Concepts from Images and Videos via Concept-prompt Binding
Xianghao Kong, Zeyu Zhang, Yuwei Guo +3
Visual concept composition, which aims to integrate different elements from images and videos into a single, coherent visual output, still falls short in accurately extracting comp…
Taming Flow-based I2V Models for Creative Video Editing
Xianghao Kong, Hansheng Chen, Yuwei Guo +4
Although image editing techniques have advanced significantly, video editing, which aims to manipulate videos according to user intent, remains an emerging challenge. Most existing…
ProFashion: Prototype-guided Fashion Video Generation with Multiple Reference Images
Xianghao Kong, Qiaosong Qi, Yuanbin Wang +3
Fashion video generation aims to synthesize temporally consistent videos from reference images of a designated character. Despite significant progress, existing diffusion-based met…
Generative AI for Film Creation: A Survey of Recent Advances
Ruihan Zhang, Borou Yu, Jiajian Min +22
Generative AI (GenAI) is transforming filmmaking, equipping artists with tools like text-to-image and image-to-video diffusion, neural radiance fields, avatar generation, and 3D sy…
Controllable Navigation Instruction Generation with Chain of Thought Prompting
Xianghao Kong, Jinyu Chen, Wenguan Wang +4
Instruction generation is a vital and multidisciplinary research area with broad applications. Existing instruction generation models are limited to generating instructions in a si…
DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative Perception
Xianghao Kong, Wentao Jiang, Jinrang Jia +3
Vehicle-to-Everything (V2X) collaborative perception is crucial for autonomous driving. However, achieving high-precision V2X perception requires a significant amount of annotated…
Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception
Si Liu, Chen Gao, Yuan Chen +8
Vehicle-to-everything (V2X) autonomous driving opens up a promising direction for developing a new generation of intelligent transportation systems. Collaborative perception (CP) a…
3D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selection
Junyu Luo, Jiahui Fu, Xianghao Kong +5
3D visual grounding aims to locate the referred target object in 3D point cloud scenes according to a free-form language description. Previous methods mostly follow a two-stage par…