16 citations · 30 across the 19 of their papers we have counts for
21 papers
ThinkRL-Edit: Thinking in Reinforcement Learning for Reasoning-Centric Image Editing
Hengjia Li, Liming Jiang, Qing Yan +6
Instruction-driven image editing with unified multimodal generative models has advanced rapidly, yet their underlying visual reasoning remains limited, leading to suboptimal perfor…
PhyRPR: Training-Free Physics-Constrained Video Generation
Yibo Zhao, Hengjia Li, Xiaofei He +1
Recent diffusion-based video generation models can synthesize visually plausible videos, yet they often struggle to satisfy physical constraints. A key reason is that most existing…
Singing Timbre Popularity Assessment Based on Multimodal Large Foundation Model
Zihao Wang, Ruibin Yuan, Ziqi Geng +7
Automated singing assessment is crucial for education and entertainment. However, existing systems face two fundamental limitations: reliance on reference tracks, which stifles cre…
MagicView: Multi-View Consistent Identity Customization via Priors-Guided In-Context Learning
Hengjia Li, Jianjin Xu, Keli Cheng +5
Recent advances in personalized generative models have demonstrated impressive capabilities in producing identity-consistent images of the same individual across diverse scenes. Ho…
RULER-Bench: Probing Rule-based Reasoning Abilities of Next-level Video Generation Models for Vision Foundation Intelligence
Xuming He, Zehao Fan, Hengjia Li +7
Recent advances in video generation have enabled the synthesis of videos with strong temporal consistency and impressive visual quality, marking a crucial step toward vision founda…
RoadBench: A Vision-Language Foundation Model and Benchmark for Road Damage Understanding
Xi Xiao, Yunbei Zhang, Janet Wang +9
Accurate road damage detection is crucial for timely infrastructure maintenance and public safety, but existing vision-only datasets and models lack the rich contextual understandi…
MagicID: Hybrid Preference Optimization for ID-Consistent and Dynamic-Preserved Video Customization
Hengjia Li, Lifan Jiang, Xi Xiao +4
Video identity customization seeks to produce high-fidelity videos that maintain consistent identity and exhibit significant dynamics based on users' reference images. However, exi…
SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement
Yuqi Lin, Hengjia Li, Wenqi Shao +5
In this paper, we explore a principal way to enhance the quality of widely pre-existing coarse masks, enabling them to serve as reliable training data for segmentation models to re…
DreamRelation: Relation-Centric Video Customization
Yujie Wei, Shiwei Zhang, Hangjie Yuan +8
Relational video customization refers to the creation of personalized videos that depict user-specified relations between two subjects, a crucial task for comprehending real-world…
GCA-3D: Towards Generalized and Consistent Domain Adaptation of 3D Generators
Hengjia Li, Yang Liu, Yibo Zhao +9
Recently, 3D generative domain adaptation has emerged to adapt the pre-trained generator to other domains without collecting massive datasets and camera pose distributions. Typical…
PersonalVideo: High ID-Fidelity Video Customization without Dynamic and Semantic Degradation
Hengjia Li, Haonan Qiu, Shiwei Zhang +6
The current text-to-video (T2V) generation has made significant progress in synthesizing realistic general videos, but it is still under-explored in identity-specific human video g…
Searching Priors Makes Text-to-Video Synthesis Better
Haoran Cheng, Liang Peng, Linxuan Xia +5
Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle t…
Pseudo Label Refinery for Unsupervised Domain Adaptation on Cross-dataset 3D Object Detection
Zhanwei Zhang, Minghao Chen, Shuai Xiao +7
Recent self-training techniques have shown notable improvements in unsupervised domain adaptation for 3D object detection (3D UDA). These techniques typically select pseudo labels,…
LoRA-Composer: Leveraging Low-Rank Adaptation for Multi-Concept Customization in Training-Free Diffusion Models
Yang Yang, Wen Wang, Liang Peng +8
Customization generation techniques have significantly advanced the synthesis of specific concepts across varied contexts. Multi-concept customization emerges as the challenging ta…
UniHDA: A Unified and Versatile Framework for Multi-Modal Hybrid Domain Adaptation
Hengjia Li, Yang Liu, Yuqi Lin +8
Recently, generative domain adaptation has achieved remarkable progress, enabling us to adapt a pre-trained generator to a new target domain. However, existing methods simply adapt…
TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without Training
Yuqi Lin, Minghao Chen, Kaipeng Zhang +7
Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in open-vocabulary classification. The class token in the image encoder is trained to captur…
Local Conditional Controlling for Text-to-Image Diffusion Models
Yibo Zhao, Liang Peng, Yang Yang +9
Diffusion models have exhibited impressive prowess in the text-to-image task. Recent methods add image-level structure controls, e.g., edge and depth maps, to manipulate the genera…
Few-shot Hybrid Domain Adaptation of Image Generators
Hengjia Li, Yang Liu, Linxuan Xia +7
Can a pre-trained generator be adapted to the hybrid of multiple target domains and generate images with integrated attributes of them? In this work, we introduce a new task -- Few…
NormKD: Normalized Logits for Knowledge Distillation
Zhihao Chi, Tu Zheng, Hengjia Li +4
Logit based knowledge distillation gets less attention in recent years since feature based methods perform better in most cases. Nevertheless, we find it still has untapped potenti…
APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding
Hengjia Li, Tu Zheng, Zhihao Chi +5
Transformer-based networks have achieved impressive performance in 3D point cloud understanding. However, most of them concentrate on aggregating local features, but neglect to dir…
Perspective-consistent multifocus multiview 3D reconstruction of small objects
Hengjia Li, Chuong Nguyen
Image-based 3D reconstruction or 3D photogrammetry of small-scale objects including insects and biological specimens is challenging due to the use of high magnification lens with i…