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cs.CV2026

HUG-VIS: A Multimodal Benchmark for Human-centered Understanding and Generation in Visual Intelligence

Fei Ma, Zebang Cheng, Minghui Li +11

Visual intelligence seeks to perceive, interpret, and synthesize the visual world and is central to modern computer vision. Human-centered visual intelligence is especially demandi…

cs.CV2026

LottieGPT: Tokenizing Vector Animation for Autoregressive Generation

Junhao Chen, Kejun Gao, Yuehan Cui +8

Despite rapid progress in video generation, existing models are incapable of producing vector animation, a dominant and highly expressive form of multimedia on the Internet. Vector…

cs.CV2026

FineEdit: Fine-Grained Image Edit with Bounding Box Guidance

Haohang Xu, Lin Liu, Zhibo Zhang +3

Diffusion-based image editing models have achieved significant progress in real world applications. However, conventional models typically rely on natural language prompts, which o…

cs.CV2026

FineViT: Progressively Unlocking Fine-Grained Perception with Dense Recaptions

Peisen Zhao, Xiaopeng Zhang, Mingxing Xu +10

While Multimodal Large Language Models (MLLMs) have experienced rapid advancements, their visual encoders frequently remain a performance bottleneck. Conventional CLIP-based encode…

cs.CV2025

CogniEdit: Dense Gradient Flow Optimization for Fine-Grained Image Editing

Yan Li, Lin Liu, Xiaopeng Zhang +4

Instruction-based image editing with diffusion models has achieved impressive results, yet existing methods struggle with fine-grained instructions specifying precise attributes su…

cs.CV2025

LoVoRA: Text-guided and Mask-free Video Object Removal and Addition with Learnable Object-aware Localization

Zhihan Xiao, Lin Liu, Yixin Gao +4

Text-guided video editing, particularly for object removal and addition, remains a challenging task due to the need for precise spatial and temporal consistency. Existing methods o…