14 citations · 20 across the 34 of their papers we have counts for
11 papers · 1 filter
Boosting Reasoning in Large Multimodal Models via Activation Replay
Yun Xing, Xiaobin Hu, Qingdong He +4
Recently, Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective approach to incentivizing reasoning capability in Large Multimodal Models (LMMs), while…
TokenAR: Multiple Subject Generation via Autoregressive Token-level enhancement
Haiyue Sun, Qingdong He, Jinlong Peng +5
Autoregressive Model (AR) has shown remarkable success in conditional image generation. However, these approaches for multiple reference generation struggle with decoupling differe…
Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models
Yuansen Liu, Haiming Tang, Jinlong Peng +12
Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks. However, their capacity to comprehend human-centric scenes has rarely…
Once Is Enough: Lightweight DiT-Based Video Virtual Try-On via One-Time Garment Appearance Injection
Yanjie Pan, Qingdong He, Lidong Wang +2
Video virtual try-on aims to replace the clothing of a person in a video with a target garment. Current dual-branch architectures have achieved significant success in diffusion mod…
IVEBench: Modern Benchmark Suite for Instruction-Guided Video Editing Assessment
Yinan Chen, Jiangning Zhang, Teng Hu +7
Instruction-guided video editing has emerged as a rapidly advancing research direction, offering new opportunities for intuitive content transformation while also posing significan…
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection
Yuhu Bai, Jiangning Zhang, Yunkang Cao +4
With the advent of vision-language models (e.g., CLIP) in zero- and few-shot settings, CLIP has been widely applied to zero-shot anomaly detection (ZSAD) in recent research, where…
HumanVideo-MME: Benchmarking MLLMs for Human-Centric Video Understanding
Yuxuan Cai, Jiangning Zhang, Zhenye Gan +9
Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks involving both images and videos. However, their capacity to comprehen…
Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning
Qingdong He, Xueqin Chen, Chaoyi Wang +7
Instruction-based image editing (IIE) has advanced rapidly with the success of diffusion models. However, existing efforts primarily focus on simple and explicit instructions to ex…
MARRS: Masked Autoregressive Unit-based Reaction Synthesis
Yabiao Wang, Shuo Wang, Jiangning Zhang +3
This work aims at a challenging task: human action-reaction synthesis, i.e., generating human reactions conditioned on the action sequence of another person. Currently, autoregress…
UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer
Haoxuan Wang, Jinlong Peng, Qingdong He +9
With the rapid development of diffusion models in image generation, the demand for more powerful and flexible controllable frameworks is increasing. Although existing methods can g…
PixelPonder: Dynamic Patch Adaptation for Enhanced Multi-Conditional Text-to-Image Generation
Yanjie Pan, Qingdong He, Zhengkai Jiang +9
Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing ControlNet-like methods struggle…