activity
20152026
most citedExploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks

406 citations · 1.8k across the 130 of their papers we have counts for

collaborators

139 papers

cs.CV2026

Learning Accurate Segmentation Purely from Self-Supervision

Zuyao You, Zuxuan Wu, Yu-Gang Jiang

Accurately segmenting objects without any manual annotations remains one of the core challenges in computer vision. In this work, we introduce Selfment, a fully self-supervised fra…

cs.CV2026

DCDM: Divide-and-Conquer Diffusion Models for Consistency-Preserving Video Generation

Haoyu Zhao, Yuang Zhang, Junqi Cheng +5

Recent video generative models have demonstrated impressive visual fidelity, yet they often struggle with semantic, geometric, and identity consistency. In this paper, we propose a…

cs.CV2026

Efficient-LVSM: Faster, Cheaper, and Better Large View Synthesis Model via Decoupled Co-Refinement Attention

Xiaosong Jia, Yihang Sun, Junqi You +5

Feedforward models for novel view synthesis (NVS) have recently advanced by transformer-based methods like LVSM, using attention among all input and target views. In this work, we…

cs.CL2026★ 1 cited

CL-bench: A Benchmark for Context Learning

Shihan Dou, Ming Zhang, Zhangyue Yin +24

Current language models (LMs) excel at reasoning over prompts using pre-trained knowledge. However, real-world tasks are far more complex and context-dependent: models must learn f…

cs.RO2026

FRoM-W1: Towards General Humanoid Whole-Body Control with Language Instructions

Peng Li, Zihan Zhuang, Yangfan Gao +16

Humanoid robots are capable of performing various actions such as greeting, dancing and even backflipping. However, these motions are often hard-coded or specifically trained, whic…

cs.AI2026

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

Xingjun Ma, Yixu Wang, Hengyuan Xu +18

The rapid evolution of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) has driven major gains in reasoning, perception, and generation across language and…

cs.AI2026

Thinking with Deltas: Incentivizing Reinforcement Learning via Differential Visual Reasoning Policy

Shujian Gao, Yuan Wang, Jiangtao Yan +2

Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced reasoning capabilities in Large Language Models. However, adapting RLVR to multimodal domains suffe…

cs.RO2025

HiMoE-VLA: Hierarchical Mixture-of-Experts for Generalist Vision-Language-Action Policies

Zhiying Du, Bei Liu, Yaobo Liang +7

Generalist vision--language--action (VLA) policies are typically trained on heterogeneous mixtures of robot demonstrations spanning diverse embodiments, action spaces, and observat…

cs.CV2025

LRANet++: Low-Rank Approximation Network for Accurate and Efficient Text Spotting

Yuchen Su, Zhineng Chen, Yongkun Du +3

End-to-end text spotting aims to jointly optimize text detection and recognition within a unified framework. Despite significant progress, designing an accurate and efficient end-t…

cs.CV2025

FreezeVLA: Action-Freezing Attacks against Vision-Language-Action Models

Xin Wang, Jie Li, Zejia Weng +9

Vision-Language-Action (VLA) models are driving rapid progress in robotics by enabling agents to interpret multimodal inputs and execute complex, long-horizon tasks. However, their…

cs.LG2025

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Zhiheng Xi, Jixuan Huang, Chenyang Liao +20

Developing autonomous LLM agents capable of making a series of intelligent decisions to solve complex, real-world tasks is a fast-evolving frontier. Like human cognitive developmen…

cs.CV2025

StableAvatar: Infinite-Length Audio-Driven Avatar Video Generation

Shuyuan Tu, Yueming Pan, Yinming Huang +6

Current diffusion models for audio-driven avatar video generation struggle to synthesize long videos with natural audio synchronization and identity consistency. This paper present…

cs.CV2025

Multimodal Referring Segmentation: A Survey

Henghui Ding, Song Tang, Shuting He +3

Multimodal referring segmentation aims to segment target objects in visual scenes, such as images, videos, and 3D scenes, based on referring expressions in text or audio format. Th…

cs.CV2025

Multi-Prompt Progressive Alignment for Multi-Source Unsupervised Domain Adaptation

Haoran Chen, Zexiao Wang, Haidong Cao +2

Large Vision-Language Models like CLIP have become a powerful foundation for Unsupervised Domain Adaptation due to their strong zero-shot generalization. State-of-the-art methods t…

cs.CV2025

StableAnimator++: Overcoming Pose Misalignment and Face Distortion for Human Image Animation

Shuyuan Tu, Zhen Xing, Xintong Han +5

Current diffusion models for human image animation often struggle to maintain identity (ID) consistency, especially when the reference image and driving video differ significantly…

cs.CL2025

Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks

Yixin Cao, Shibo Hong, Xinze Li +24

Large Language Models (LLMs) are advancing at an amazing speed and have become indispensable across academia, industry, and daily applications. To keep pace with the status quo, th…

cs.CV2025

SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL

Junke Wang, Zhi Tian, Xun Wang +4

This work presents SimpleAR, a vanilla autoregressive visual generation framework without complex architecure modifications. Through careful exploration of training and inference o…

cs.CV2025

Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Yitong Chen, Lingchen Meng, Wujian Peng +4

Vision Foundation Models (VFMs) provide strong visual representations for a wide range of applications. In this work, we enhance prevailing VFMs through multimodal training, allowi…

cs.CV2025

Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning

Haoran Chen, Ping Wang, Zihan Zhou +3

Class-incremental learning (CIL) enables models to learn new classes progressively while preserving knowledge of previously learned ones. Recent advances in this field have shifted…

cs.CR2025★ 1 cited

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety

Xingjun Ma, Yifeng Gao, Yixu Wang +45

The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…

cs.CV2025

Cross-Modal Transferable Image-to-Video Attack on Video Quality Metrics

Georgii Gotin, Ekaterina Shumitskaya, Anastasia Antsiferova +1

Recent studies have revealed that modern image and video quality assessment (IQA/VQA) metrics are vulnerable to adversarial attacks. An attacker can manipulate a video through prep…

cs.RO2024

VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks

Shiduo Zhang, Zhe Xu, Peiju Liu +8

General-purposed embodied agents are designed to understand the users' natural instructions or intentions and act precisely to complete universal tasks. Recently, methods based on…

cs.CV2024

Comprehensive Multi-Modal Prototypes are Simple and Effective Classifiers for Vast-Vocabulary Object Detection

Yitong Chen, Wenhao Yao, Lingchen Meng +3

Enabling models to recognize vast open-world categories has been a longstanding pursuit in object detection. By leveraging the generalization capabilities of vision-language models…

cs.CV2024

CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation

Hui Zhang, Dexiang Hong, Yitong Wang +4

Diffusion models have been recognized for their ability to generate images that are not only visually appealing but also of high artistic quality. As a result, Layout-to-Image (L2I…