collaborators
Showing cs.CVShow all

24 papers · 1 filter

cs.CV2026

PIGEONS: Incremental Long-Video Captioning with Persistent Identity Gallery and Evolving Overarching Narrative Summary

Xinlong Chen, Weihong Lin, Yuanxing Zhang +9

Detailed video captioning has become an essential semantic interface for multi-modal understanding and generation. While existing methods mainly target short videos, extending them…

cs.CV2026

PortraitAes: Intent-Conditioned Structured Portrait Aesthetic Assessment

Junzhou Xie, Haozhong Xiong, Xunyun Tian +8

Portrait aesthetic assessment assigns comparable scores according to how effectively human-centered images fulfill their photographic intent. These scores support data filtering, c…

cs.CV2026

Human-Centric Image Captioning with Subject-Centered Spatial Understanding

Bozhou Li, Jiahang Zhang, Yue Ding +11

While multimodal large language models (MLLMs) achieve remarkable performance on generic image captioning, they frequently suffer from structural hallucinations in human-centric sc…

cs.CV2026

UniSwap: Streaming Audio-Visual Identity Swapping for Talking Videos

Yuxuan Zhang, Haozhong Xiong, Jiayi Song +5

Talking-video character replacement requires coordinated transfer of appearance and voice while preserving the source motion, scene, linguistic content, and audio-video timing. Exi…

cs.CV2026

FocusMem: Factorizing Content, Readout, and Trust in Latent GUI Memory

Zhuoran Zhang, Bowen Li, Jingcheng Ju +5

GUI agents must remember both useful experience from earlier tasks and unfinished progress in the current interaction. Latent memory offers a compact solution by compressing multim…

cs.CV2026

OmniPack: Unified Token Compression for Efficient Omni-modal Large Language Models

Wanshun Su, Yang Shi, Feihu Liu +10

Omni-modal large language models (Omni-LLMs) have achieved remarkable performance on audio-visual understanding tasks, but processing long and highly redundant visual and audio tok…

cs.CV2026

Beacon: Knowing When and How to Perform Agentic Visual Reasoning

Qixun Wang, Yang Shi, Letian Cheng +11

The fundamental goal of agentic visual reasoning is to improve the success rate of multimodal large language models (MLLMs) on complex tasks. We rethink agentic visual reasoning th…

cs.CV2026

RefCaptioner: Multi-Reference Image-Grounded Video Captioning

Tengfei Liu, Yang Shi, Yuran Wang +16

Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple reference images. We introduce multi-…

cs.CV2026

Rethinking Classifier-Free Guidance in On-Policy Diffusion Distillation

Bingnan Li, Haozhe Wang, Haozhong Xiong +5

On-policy distillation (OPD) adapts diffusion models by querying a teacher along trajectories generated by the current student, but how it should behave under classifier-free guida…

cs.CV2026

Beyond Zooming: Learning Multi-Tool Visual Reasoning for Ultra-High-Resolution Remote Sensing

Fengxiang Wang, Jiangnan Huang, Mingshuo Chen +8

Ultra-high-resolution (UHR) remote-sensing (RS) imagery provides fine-grained Earth-observation evidence over city-scale scenes, but poses a fundamental challenge for multimodal la…

cs.CV2026

ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships

Xinyu Liu, Shihao Li, Weihong Lin +10

Recent diffusion-based video generation models have made significant progress in multi-reference image-conditioned video editing. However, existing methods still struggle to coordi…

cs.CV2026

KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation

Yuqi Tang, Tengfei Liu, Yizheng Lai +18

Video generation increasingly relies on keyframe-based workflows, where creators specify a sequence of reference images to guide generation. Although recent models support multi-ke…

cs.CV2026

MultiRef-Compass: Towards Comprehensive Evaluation of Multi-Reference-to-Audio-Video Generation

Xiaohan Zhang, Yuqing Wen, Junlin Chen +9

Multi-reference-to-audio-video (MR2AV) generation aims to generate coherent audio-video content conditioned on multiple references and textual instructions. Existing benchmarks mai…

cs.CV2026

MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation

Yujie Wei, Yujin Han, Zhekai Chen +20

Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However, evaluating such frontier mo…

cs.CV2026

CapRiCorn-1K: A Comprehensive Benchmark for Video Captioning and Subject Referential Consistency Across Temporal Scales

Xinlong Chen, Jiafu Tang, Yue Ding +12

Accurate and comprehensive video captions with consistent subject references are critical for downstream understanding and generation tasks. However, few existing benchmarks can ob…

cs.CV2026

LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV

Tengfei Liu, Yang Shi, Xuanyu Zhu +17

Audio-visual generation is rapidly advancing from short clips to minute-long content, while existing evaluation protocols remain largely confined to short-form settings. Existing b…

cs.CV2026

Semantic Granularity Navigation in Image Editing

Liangsi Lu, Minzhe Guo, Xuhang Chen +1

Despite the generative capabilities of diffusion and flow models, real-image editing remains constrained by a persistent trade-off between semantic editability and structural fidel…

cs.CV2026

Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos

Yuqi Tang, Yang Shi, Zhuoran Zhang +21

Recent video generative models have greatly improved the realism of AI-generated videos, yet their outputs still exhibit artifacts such as temporal inconsistencies, structural dist…

cs.CV2026

Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling

Xuehai Bai, Yang Shi, Yi-Fan Zhang +7

Recent image editing models have achieved remarkable progress in instruction following, multimodal understanding, and complex visual editing. However, existing benchmarks often fai…

cs.CV2026

Beyond the Last Layer: Multi-Layer Representation Fusion for Visual Tokenization

Xuanyu Zhu, Yan Bai, Yang Shi +4

Representation autoencoders that reuse frozen pretrained vision encoders as visual tokenizers have achieved strong reconstruction and generation quality. However, existing methods…

cs.CV2026

Research on World Models Is Not Merely Injecting World Knowledge into Specific Tasks

Bohan Zeng, Kaixin Zhu, Daili Hua +24

World models have emerged as a critical frontier in AI research, aiming to enhance large models by infusing them with physical dynamics and world knowledge. The core objective is t…

cs.CV2025

AVoCaDO: An Audiovisual Video Captioner Driven by Temporal Orchestration

Xinlong Chen, Yue Ding, Weihong Lin +9

Audiovisual video captioning aims to generate semantically rich descriptions with temporal alignment between visual and auditory events, thereby benefiting both video understanding…

cs.CV2025

BaseReward: A Strong Baseline for Multimodal Reward Model

Yi-Fan Zhang, Haihua Yang, Huanyu Zhang +11

The rapid advancement of Multimodal Large Language Models (MLLMs) has made aligning them with human preferences a critical challenge. Reward Models (RMs) are a core technology for…

cs.CV2025

OpenGPT-4o-Image: A Comprehensive Dataset for Advanced Image Generation and Editing

Zhihong Chen, Xuehai Bai, Yang Shi +9

The performance of unified multimodal models for image generation and editing is fundamentally constrained by the quality and comprehensiveness of their training data. While existi…