68 citations · 124 across the 17 of their papers we have counts for
12 papers · 1 filter
MIRA: Multimodal Iterative Reasoning Agent for Image Editing
Ziyun Zeng, Hang Hua, Jiebo Luo
Instruction-guided image editing offers an intuitive way for users to edit images with natural language. However, diffusion-based editing models often struggle to accurately interp…
MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models
Hang Hua, Ziyun Zeng, Yizhi Song +5
Recent multimodal image generators such as GPT-4o, Gemini 2.0 Flash, and Gemini 2.5 Pro excel at following complex instructions, editing images and maintaining concept consistency.…
The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Lei Sun +143
This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep mode…
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity
Hang Hua, Qing Liu, Lingzhi Zhang +5
The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal tasks, enabling more sophisticated and accurate reasoning across various applications, inclu…
MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models
Hang Hua, Yunlong Tang, Ziyun Zeng +5
The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal understanding, enabling more sophisticated and accurate integration of visual and textual in…
PromptFix: You Prompt and We Fix the Photo
Yongsheng Yu, Ziyun Zeng, Hang Hua +2
Diffusion models equipped with language models demonstrate excellent controllability in image generation tasks, allowing image processing to adhere to human instructions. However,…
FINEMATCH: Aspect-based Fine-grained Image and Text Mismatch Detection and Correction
Hang Hua, Jing Shi, Kushal Kafle +5
Recent progress in large-scale pre-training has led to the development of advanced vision-language models (VLMs) with remarkable proficiency in comprehending and generating multimo…
V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuning
Hang Hua, Yolo Yunlong Tang, Chenliang Xu +1
Video summarization aims to create short, accurate, and cohesive summaries of longer videos. Despite the existence of various video summarization datasets, a notable limitation is…
Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding
Yolo Yunlong Tang, Daiki Shimada, Jing Bi +3
Large language models (LLMs) have demonstrated remarkable capabilities in natural language and multimodal domains. By fine-tuning multimodal LLMs with temporal annotations from wel…
GaussianStyle: Gaussian Head Avatar via StyleGAN
Pinxin Liu, Luchuan Song, Daoan Zhang +5
Existing methods like Neural Radiation Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made significant strides in facial attribute control such as facial animation and compone…
VideoXum: Cross-modal Visual and Textural Summarization of Videos
Jingyang Lin, Hang Hua, Ming Chen +4
Video summarization aims to distill the most important information from a source video to produce either an abridged clip or a textual narrative. Traditionally, different methods h…
PromptCap: Prompt-Guided Task-Aware Image Captioning
Yushi Hu, Hang Hua, Zhengyuan Yang +3
Knowledge-based visual question answering (VQA) involves questions that require world knowledge beyond the image to yield the correct answer. Large language models (LMs) like GPT-3…