20 citations · 40 across the 32 of their papers we have counts for
34 papers
W2Rep: Learning Visual Representations by Watching the World Change
Wen Huang, Hang Guo, Jiarui Yang +3
Images capture the world at one moment, whereas video reveals how it changes. Image self-supervision learns spatial structure from a single moment, while video methods commonly lea…
TTTIR: Unlocking Instance-Specific State Evolution via Test-Time Training for Image Restoration
Kaihang Zheng, Jun Li, Hang Guo +5
Image restoration is inherently challenging due to the diverse and highly input-dependent nature of real-world degradations. While recent architectures like Transformers and state-…
GDLAM: Group-Disentangled Latent Action Model for Highly Disentangled Embodied Pretraining
Jiarui Yang, Jiawei Li, Jiale Zhang +5
Latent action models (LAMs) learn action-related representations from action-free videos via self-supervised future prediction, offering a scalable paradigm for embodied intelligen…
Beyond Illumination: A Conditional Mutual Information-Guided Network for Low-Light Image Enhancement
Ya-nan Guan, Shaonan Zhang, Tao Dai +5
Low-light image enhancement (LLIE) seeks to restore structural fidelity, natural color rendition, and proper exposure from images captured under inadequate lighting conditions. Rec…
ARBOR: Online Process Rewards via a Reusable Rubric Buffer for Search Agents
Zheng Liu, Longxiang Zhang, Xintong Wang +8
LLM-based search agents are trained predominantly with outcome-only reward, leaving the search process itself unsupervised. This signal degenerates on outcome-homogeneous groups wh…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)
Ya-nan Guan, Shaonan Zhang, Hang Guo +55
In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI Flash Portrait. Despite sign…
CASL: Curvature-Augmented Self-supervised Learning for 3D Anomaly Detection
Yaohua Zha, Xue Yuerong, Chunlin Fan +4
Deep learning-based 3D anomaly detection methods have demonstrated significant potential in industrial manufacturing. However, many approaches are specifically designed for anomaly…
JPRO: Automated Multimodal Jailbreaking via Multi-Agent Collaboration Framework
Yuxuan Zhou, Yang Bai, Kuofeng Gao +2
The widespread application of large VLMs makes ensuring their secure deployment critical. While recent studies have demonstrated jailbreak attacks on VLMs, existing approaches are…
Improving Deepfake Detection with Reinforcement Learning-Based Adaptive Data Augmentation
Yuxuan Zhou, Tao Yu, Wen Huang +3
The generalization capability of deepfake detectors is critical for real-world use. Data augmentation via synthetic fake face generation effectively enhances generalization, yet cu…
Why Does Weak-OOD Help? A Further Step Towards Understanding Jailbreaking VLMs
Yuxuan Zhou, Yuzhao Peng, Yang Bai +7
Large Vision-Language Models (VLMs) are susceptible to jailbreak attacks: researchers have developed various attack strategies that bypass the safety mechanisms of VLMs. Among thes…
PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter
Yaohua Zha, Yanzi Wang, Hang Guo +7
Applying pre-trained models to assist point cloud understanding has recently become a mainstream paradigm in 3D perception. However, existing application strategies are straightfor…
Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning
Jinpeng Wang, Tianci Luo, Yaohua Zha +7
Visual In-Context Learning (VICL) enables adaptively solving vision tasks by leveraging pixel demonstrations, mimicking human-like task completion through analogy. Prompt selection…
Protecting Your Video Content: Disrupting Automated Video-based LLM Annotations
Haitong Liu, Kuofeng Gao, Yang Bai +4
Recently, video-based large language models (video-based LLMs) have achieved impressive performance across various video comprehension tasks. However, this rapid advancement raises…
FastVAR: Linear Visual Autoregressive Modeling via Cached Token Pruning
Hang Guo, Yawei Li, Taolin Zhang +4
Visual Autoregressive (VAR) modeling has gained popularity for its shift towards next-scale prediction. However, existing VAR paradigms process the entire token map at each scale s…
MambaIRv2: Attentive State Space Restoration
Hang Guo, Yong Guo, Yaohua Zha +5
The Mamba-based image restoration backbones have recently demonstrated significant potential in balancing global reception and computational efficiency. However, the inherent causa…
BoostAdapter: Improving Vision-Language Test-Time Adaptation via Regional Bootstrapping
Taolin Zhang, Jinpeng Wang, Hang Guo +3
Adaptation of pretrained vision-language models such as CLIP to various downstream tasks have raised great interest in recent researches. Previous works have proposed a variety of…
Towards Scalable Semantic Representation for Recommendation
Taolin Zhang, Junwei Pan, Jinpeng Wang +9
With recent advances in large language models (LLMs), there has been emerging numbers of research in developing Semantic IDs based on LLMs to enhance the performance of recommendat…
ReFIR: Grounding Large Restoration Models with Retrieval Augmentation
Hang Guo, Tao Dai, Zhihao Ouyang +4
Recent advances in diffusion-based Large Restoration Models (LRMs) have significantly improved photo-realistic image restoration by leveraging the internal knowledge embedded withi…
IntLoRA: Integral Low-rank Adaptation of Quantized Diffusion Models
Hang Guo, Yawei Li, Tao Dai +2
Fine-tuning pre-trained diffusion models under limited budgets has gained great success. In particular, the recent advances that directly fine-tune the quantized weights using Low-…
Point Cloud Mixture-of-Domain-Experts Model for 3D Self-supervised Learning
Yaohua Zha, Tao Dai, Hang Guo +4
Point clouds, as a primary representation of 3D data, can be categorized into scene domain point clouds and object domain point clouds. Point cloud self-supervised learning (SSL) h…
Large Point-to-Gaussian Model for Image-to-3D Generation
Longfei Lu, Huachen Gao, Tao Dai +4
Recently, image-to-3D approaches have significantly advanced the generation quality and speed of 3D assets based on large reconstruction models, particularly 3D Gaussian reconstruc…
Pre-training Point Cloud Compact Model with Partial-aware Reconstruction
Yaohua Zha, Yanzi Wang, Tao Dai +1
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited substantial improvements across various tasks. However, two drawbacks hinder their practical ap…
CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks
Hao Fang, Jiawei Kong, Bin Chen +3
Transferable targeted adversarial attacks aim to mislead models into outputting adversary-specified predictions in black-box scenarios. Recent studies have introduced \textit{singl…
MambaVC: Learned Visual Compression with Selective State Spaces
Shiyu Qin, Jinpeng Wang, Yimin Zhou +6
Learned visual compression is an important and active task in multimedia. Existing approaches have explored various CNN- and Transformer-based designs to model content distribution…