20 citations · 44 across the 37 of their papers we have counts for
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Beyond Pattern Matching in 3D MLLMs: Part-Level Functional Reasoning for Generalizable Recognition
Weihong Li, Hao Jiang, Yaohua Zha +2
3D MLLMs recognize objects via pattern matching, which fails when geometrically similar objects require functional reasoning to disambiguate (e.g., dresser vs. wardrobe). Our per-s…
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…
LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models
Jiarui Yang, Jiale Zhange, Jiawei Li +5
World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied intelligence remains limited by…
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…
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…
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…
Personalized Face Super-Resolution with Identity Decoupling and Fitting
Jiarui Yang, Hang Guo, Wen Huang +2
In recent years, face super-resolution (FSR) methods have achieved remarkable progress, generally maintaining high image fidelity and identity (ID) consistency under standard setti…
RelayFormer: A Unified Local-Global Attention Framework for Scalable Image and Video Manipulation Localization
Wen Huang, Jiarui Yang, Tao Dai +4
Visual manipulation localization (VML) aims to identify tampered regions in images and videos, a task that has become increasingly challenging with the rise of advanced editing too…
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…
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…
Diffusion Prior Interpolation for Flexibility Real-World Face Super-Resolution
Jiarui Yang, Tao Dai, Yufei Zhu +3
Diffusion models represent the state-of-the-art in generative modeling. Due to their high training costs, many works leverage pre-trained diffusion models' powerful representations…
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…
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…
Invertible Residual Rescaling Models
Jinmin Li, Tao Dai, Yaohua Zha +6
Invertible Rescaling Networks (IRNs) and their variants have witnessed remarkable achievements in various image processing tasks like image rescaling. However, we observe that IRNs…
Boundary-aware Decoupled Flow Networks for Realistic Extreme Rescaling
Jinmin Li, Tao Dai, Jingyun Zhang +5
Recently developed generative methods, including invertible rescaling network (IRN) based and generative adversarial network (GAN) based methods, have demonstrated exceptional perf…
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling
Yaohua Zha, Naiqi Li, Yanzi Wang +6
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited substantial improvements across various tasks. However, these models heavily rely on the Transf…
MambaIR: A Simple Baseline for Image Restoration with State-Space Model
Hang Guo, Jinmin Li, Tao Dai +3
Recent years have seen significant advancements in image restoration, largely attributed to the development of modern deep neural networks, such as CNNs and Transformers. However,…