8 citations · 10 across the 21 of their papers we have counts for
24 papers
Risk-minimizing GUE-implementations of truthful reporting in a Dynamic Social Choice Problem
Endre Csóka, Máté Viczián
The Guaranteed Utility Mechanism (GUM) was introduced to implement efficiency in Guaranteed Utility Equilibrium (GUE) in dynamic social choice problems. We show that this mechanism…
DIET: Deletion-response Expert Trimming for Video Diffusion Transformers
Jiachang Zhang, Teng Hu, Bohao Feng +4
Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storage remains costly. Existing o…
TRACE-Bench: Decomposing and Diagnosing Multi-Reference Image Generation
Haoran Wang, Chaofan Ma, Ran Yi +1
Despite recent advances in unified multimodal models for multi-reference image generation, existing benchmarks remain organized around predefined task types (e.g., "subject composi…
Efficient Audio-Visual Generation via Synchrony-Aware Cross-Modal Sparse Attention
Shengchuan Gao, Teng Hu, Bohao Feng +4
Recent audio-visual generation models can synthesize synchronized video and sound in a unified diffusion process, but their inference cost remains high because long video token seq…
PhysAgent: Reflective Agentic Physics Control for Physically Plausible Video Generation
Qirui Li, Jinkun Hao, Yibo Li +3
Recent advances in physics-grounded video generation leverage physics simulation as a physical prior to guide video synthesis toward physically plausible outcomes. The simulation p…
Cycle-World: Mitigating Error Accumulation in Long-term Video World Models via Reverse-Prediction Cycle Consistency
Zihan Su, Teng Hu, Jiangning Zhang +4
Autoregressive diffusion models have enabled high-quality video generation, yet their sequential nature inherently suffers from error accumulation. In long-horizon video synthesis,…
MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data
Teng Hu, Mingchun Lu, Yating Wang +6
Video world models are a foundational generative technology for embodied AI and the Metaverse, yet existing approaches are inherently limited to a single agent observing from a sin…
Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory
Jinzhuo Liu, Jiangning Zhang, Wencan Jiang +5
Autoregressive video generation has improved rapidly in visual fidelity and interactivity, but it still suffers from long-term inconsistency and memory degradation. Most existing s…
Evolution of Video Generative Foundations
Teng Hu, Jiangning Zhang, Hongrui Huang +7
The rapid advancement of Artificial Intelligence Generated Content (AIGC) has revolutionized video generation, enabling systems ranging from proprietary pioneers like OpenAI's Sora…
UniICL: Systematizing Unified Multimodal In-context Learning through a Capability-Oriented Taxonomy
Yicheng Xu, Jiangning Zhang, Zhucun Xue +5
In-context learning (ICL) enables fast task adaptation from demonstrations without per-task parameter updates but remains highly sensitive to example selection and formatting. In u…
PoseAnything: Universal Pose-guided Video Generation with Part-aware Temporal Coherence
Ruiyan Wang, Teng Hu, Kaihui Huang +3
Pose-guided video generation refers to controlling the motion of subjects in generated video through a sequence of poses. It enables precise control over subject motion and has imp…
InstanceV: Instance-Level Video Generation
Yuheng Chen, Teng Hu, Jiangning Zhang +3
Recent advances in text-to-video diffusion models have enabled the generation of high-quality videos conditioned on textual descriptions. However, most existing text-to-video model…
Harmony: Harmonizing Audio and Video Generation through Cross-Task Synergy
Teng Hu, Zhentao Yu, Guozhen Zhang +6
The synthesis of synchronized audio-visual content is a key challenge in generative AI, with open-source models facing challenges in robust audio-video alignment. Our analysis reve…
UltraGen: High-Resolution Video Generation with Hierarchical Attention
Teng Hu, Jiangning Zhang, Zihan Su +1
Recent advances in video generation have made it possible to produce visually compelling videos, with wide-ranging applications in content creation, entertainment, and virtual real…
IAR2: Improving Autoregressive Visual Generation with Semantic-Detail Associated Token Prediction
Ran Yi, Teng Hu, Zihan Su +2
Autoregressive models have emerged as a powerful paradigm for visual content creation, but often overlook the intrinsic structural properties of visual data. Our prior work, IAR, i…
PolyVivid: Vivid Multi-Subject Video Generation with Cross-Modal Interaction and Enhancement
Teng Hu, Zhentao Yu, Zhengguang Zhou +4
Despite recent advances in video generation, existing models still lack fine-grained controllability, especially for multi-subject customization with consistent identity and intera…
Image Inversion: A Survey from GANs to Diffusion and Beyond
Yinan Chen, Jiangning Zhang, Yali Bi +6
Image inversion is a fundamental task in generative models, aiming to map images back to their latent representations to enable downstream applications such as editing, restoration…
Improving Autoregressive Visual Generation with Cluster-Oriented Token Prediction
Teng Hu, Jiangning Zhang, Ran Yi +5
Employing LLMs for visual generation has recently become a research focus. However, the existing methods primarily transfer the LLM architecture to visual generation but rarely inv…
AttentionPainter: An Efficient and Adaptive Stroke Predictor for Scene Painting
Yizhe Tang, Yue Wang, Teng Hu +5
Stroke-based Rendering (SBR) aims to decompose an input image into a sequence of parameterized strokes, which can be rendered into a painting that resembles the input image. Recent…
SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
Teng Hu, Jiangning Zhang, Ran Yi +3
In recent years, the development of diffusion models has led to significant progress in image and video generation tasks, with pre-trained models like the Stable Diffusion series p…
SuperSVG: Superpixel-based Scalable Vector Graphics Synthesis
Teng Hu, Ran Yi, Baihong Qian +3
SVG (Scalable Vector Graphics) is a widely used graphics format that possesses excellent scalability and editability. Image vectorization, which aims to convert raster images to SV…
MotionMaster: Training-free Camera Motion Transfer For Video Generation
Teng Hu, Jiangning Zhang, Ran Yi +5
The emergence of diffusion models has greatly propelled the progress in image and video generation. Recently, some efforts have been made in controllable video generation, includin…
SAMVG: A Multi-stage Image Vectorization Model with the Segment-Anything Model
Haokun Zhu, Juang Ian Chong, Teng Hu +3
Vector graphics are widely used in graphical designs and have received more and more attention. However, unlike raster images which can be easily obtained, acquiring high-quality v…
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model
Teng Hu, Jiangning Zhang, Ran Yi +5
Anomaly inspection plays an important role in industrial manufacture. Existing anomaly inspection methods are limited in their performance due to insufficient anomaly data. Althoug…