activity
20212026
most citedProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

8 citations · 13 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2026

Rethinking Token Reduction for Large Vision-Language Models

Yi Wang, Haofei Zhang, Qihan Huang +7

Large Vision-Language Models (LVLMs) excel in visual understanding and reasoning, but the excessive visual tokens lead to high inference costs. Although recent token reduction meth…

cs.CV2025

Syn-GRPO: Self-Evolving Data Synthesis for MLLM Perception Reasoning

Qihan Huang, Haofei Zhang, Rong Wei +4

RL (reinforcement learning) methods (e.g., GRPO) for MLLM (Multimodal LLM) perception ability has attracted wide research interest owing to its remarkable generalization ability. N…

cs.CV2025

Boosting MLLM Reasoning with Text-Debiased Hint-GRPO

Qihan Huang, Weilong Dai, Jinlong Liu +6

MLLM reasoning has drawn widespread research for its excellent problem-solving capability. Current reasoning methods fall into two types: PRM, which supervises the intermediate rea…

cs.CV2025

CustomVideoX: 3D Reference Attention Driven Dynamic Adaptation for Zero-Shot Customized Video Diffusion Transformers

D. She, Mushui Liu, Jingxuan Pang +9

Customized generation has achieved significant progress in image synthesis, yet personalized video generation remains challenging due to temporal inconsistencies and quality degrad…

cs.CV2024

PatchDPO: Patch-level DPO for Finetuning-free Personalized Image Generation

Qihan Huang, Weilong Dai, Jinlong Liu +4

Finetuning-free personalized image generation can synthesize customized images without test-time finetuning, attracting wide research interest owing to its high efficiency. Current…

cs.CV2024

LG-CAV: Train Any Concept Activation Vector with Language Guidance

Qihan Huang, Jie Song, Mengqi Xue +6

Concept activation vector (CAV) has attracted broad research interest in explainable AI, by elegantly attributing model predictions to specific concepts. However, the training of C…

cs.CV2024

Resolving Multi-Condition Confusion for Finetuning-Free Personalized Image Generation

Qihan Huang, Siming Fu, Jinlong Liu +3

Personalized text-to-image generation methods can generate customized images based on the reference images, which have garnered wide research interest. Recent methods propose a fin…

cs.CV2024★ 1 cited

MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Xierui Wang, Siming Fu, Qihan Huang +2

Recent advancements in text-to-image generation models have dramatically enhanced the generation of photorealistic images from textual prompts, leading to an increased interest in…

cs.CV2024

On the Concept Trustworthiness in Concept Bottleneck Models

Qihan Huang, Jie Song, Jingwen Hu +3

Concept Bottleneck Models (CBMs), which break down the reasoning process into the input-to-concept mapping and the concept-to-label prediction, have garnered significant attention…

cs.CV2022★ 4 cited

Evaluation and Improvement of Interpretability for Self-Explainable Part-Prototype Networks

Qihan Huang, Mengqi Xue, Wenqi Huang +4

Part-prototype networks (e.g., ProtoPNet, ProtoTree, and ProtoPool) have attracted broad research interest for their intrinsic interpretability and comparable accuracy to non-inter…

cs.CV2022★ 8 cited

ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

Mengqi Xue, Qihan Huang, Haofei Zhang +4

Prototypical part network (ProtoPNet) has drawn wide attention and boosted many follow-up studies due to its self-explanatory property for explainable artificial intelligence (XAI)…

cs.CV2021

A Survey of Deep Learning for Low-Shot Object Detection

Qihan Huang, Haofei Zhang, Mengqi Xue +2

Object detection has achieved a huge breakthrough with deep neural networks and massive annotated data. However, current detection methods cannot be directly transferred to the sce…