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20232026
most citedTouchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

2 citations · 10 across the 39 of their papers we have counts for

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cs.CV2026

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

Keming Wu, Zuhao Yang, Kaichen Zhang +24

Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning…

cs.CV2025

4D-VGGT: A General Foundation Model with SpatioTemporal Awareness for Dynamic Scene Geometry Estimation

Haonan Wang, Hanyu Zhou, Haoyue Liu +1

We investigate a challenging task of dynamic scene geometry estimation, which requires representing both spatial and temporal features. Typically, existing methods align the two fe…

cs.CV2025

A Cognitive Process-Inspired Architecture for Subject-Agnostic Brain Visual Decoding

Jingyu Lu, Haonan Wang, Qixiang Zhang +1

Subject-agnostic brain decoding, which aims to reconstruct continuous visual experiences from fMRI without subject-specific training, holds great potential for clinical application…

cs.CV2025

ZEBRA: Towards Zero-Shot Cross-Subject Generalization for Universal Brain Visual Decoding

Haonan Wang, Jingyu Lu, Hongrui Li +1

Recent advances in neural decoding have enabled the reconstruction of visual experiences from brain activity, positioning fMRI-to-image reconstruction as a promising bridge between…

cs.CV2025

Switchable Token-Specific Codebook Quantization For Face Image Compression

Yongbo Wang, Haonan Wang, Guodong Mu +7

With the ever-increasing volume of visual data, the efficient and lossless transmission, along with its subsequent interpretation and understanding, has become a critical bottlenec…

cs.CV2025

Injecting Frame-Event Complementary Fusion into Diffusion for Optical Flow in Challenging Scenes

Haonan Wang, Hanyu Zhou, Haoyue Liu +1

Optical flow estimation has achieved promising results in conventional scenes but faces challenges in high-speed and low-light scenes, which suffer from motion blur and insufficien…

cs.CV2025

TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking

Mengmeng Wang, Haonan Wang, Yulong Li +4

3D LiDAR-based single object tracking (SOT) relies on sparse and irregular point clouds, posing challenges from geometric variations in scale, motion patterns, and structural compl…

cs.CV2025

STD-GS: Exploring Frame-Event Interaction for SpatioTemporal-Disentangled Gaussian Splatting to Reconstruct High-Dynamic Scene

Hanyu Zhou, Haonan Wang, Haoyue Liu +3

High-dynamic scene reconstruction aims to represent static background with rigid spatial features and dynamic objects with deformed continuous spatiotemporal features. Typically, e…

cs.CV2025

Fostering Video Reasoning via Next-Event Prediction

Haonan Wang, Hongfu Liu, Xiangyan Liu +4

Next-token prediction serves as the foundational learning task enabling reasoning in LLMs. But what should the learning task be when aiming to equip MLLMs with temporal reasoning c…

cs.CV2025

CONCORD: Concept-Informed Diffusion for Dataset Distillation

Jianyang Gu, Haonan Wang, Ruoxi Jia +4

Dataset distillation (DD) has witnessed significant progress in creating small datasets that encapsulate rich information from large original ones. Particularly, methods based on g…

cs.CV2025

UniEval: Unified Holistic Evaluation for Unified Multimodal Understanding and Generation

Yi Li, Haonan Wang, Qixiang Zhang +4

The emergence of unified multimodal understanding and generation models is rapidly attracting attention because of their ability to enhance instruction-following capabilities while…

cs.CV2025★ 2 cited

Multi-Modal Explainable Medical AI Assistant for Trustworthy Human-AI Collaboration

Honglong Yang, Shanshan Song, Yi Qin +6

Generalist Medical AI (GMAI) systems have demonstrated expert-level performance in biomedical perception tasks, yet their clinical utility remains limited by inadequate multi-modal…

cs.CV2025

DD-Ranking: Rethinking the Evaluation of Dataset Distillation

Zekai Li, Xinhao Zhong, Samir Khaki +49

In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance co…

cs.CV2025

Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks

Haonan Wang, Jiaji Mao, Lehan Wang +11

Accurate segmentation of tumors and organs-at-risk is essential for oncology but remains time-consuming and expertise-intensive. Existing AI systems often require manual spatial pr…

cs.CV2025

NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation

Xiangyan Liu, Jinjie Ni, Zijian Wu +5

Recent advances in reinforcement learning (RL) have strengthened the reasoning capabilities of vision-language models (VLMs). However, enhancing policy exploration to better scale…

cs.CV2025

Bridge Frame and Event: Common Spatiotemporal Fusion for High-Dynamic Scene Optical Flow

Hanyu Zhou, Haonan Wang, Haoyue Liu +3

High-dynamic scene optical flow is a challenging task, which suffers spatial blur and temporal discontinuous motion due to large displacement in frame imaging, thus deteriorating t…

cs.CV2025

Neurons: Emulating the Human Visual Cortex Improves Fidelity and Interpretability in fMRI-to-Video Reconstruction

Haonan Wang, Qixiang Zhang, Lehan Wang +2

Decoding visual stimuli from neural activity is essential for understanding the human brain. While fMRI methods have successfully reconstructed static images, fMRI-to-video reconst…

cs.CV2024★ 2 cited

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…

cs.CV2024★ 1 cited

Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks

Lehan Wang, Haonan Wang, Honglong Yang +4

Several medical Multimodal Large Languange Models (MLLMs) have been developed to address tasks involving visual images with textual instructions across various medical modalities,…

cs.CV2024

GTPT: Group-based Token Pruning Transformer for Efficient Human Pose Estimation

Haonan Wang, Jie Liu, Jie Tang +4

In recent years, 2D human pose estimation has made significant progress on public benchmarks. However, many of these approaches face challenges of less applicability in the industr…

cs.CV2024★ 2 cited

S&D Messenger: Exchanging Semantic and Domain Knowledge for Generic Semi-Supervised Medical Image Segmentation

Qixiang Zhang, Haonan Wang, Xiaomeng Li

Semi-supervised medical image segmentation (SSMIS) has emerged as a promising solution to tackle the challenges of time-consuming manual labeling in the medical field. However, in…

cs.CV2024

ADLDA: A Method to Reduce the Harm of Data Distribution Shift in Data Augmentation

Haonan Wang

This study introduces a novel data augmentation technique, ADLDA, aimed at mitigating the negative impact of data distribution shifts caused by the data augmentation process in com…

cs.CV2024

Research on geometric figure classification algorithm based on Deep Learning

Ruiyang Wang, Haonan Wang, Junfeng Sun +2

In recent years, with the rapid development of computer information technology, the development of artificial intelligence has been accelerating. The traditional geometry recogniti…

cs.CV2023★ 1 cited

Efficient Dataset Distillation via Minimax Diffusion

Jianyang Gu, Saeed Vahidian, Vyacheslav Kungurtsev +4

Dataset distillation reduces the storage and computational consumption of training a network by generating a small surrogate dataset that encapsulates rich information of the origi…