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20232026
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cs.CV2026

Not All Tasks Quantize Equally: Fisher-Guided Quantization for Visual Geometry Transformer

Yipu Zhang, Jintao Cheng, Weilun Feng +5

Feed-forward 3D reconstruction models, represented by Visual Geometry Grounded Transformer (VGGT), jointly predict multiple visual geometry tasks such as depth estimation, camera p…

cs.CV2026

Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation

Mingqiang Wu, Weilun Feng, Zhefeng Zhang +8

Autoregressive video diffusion models enable open-ended generation through local attention and KV caching. However, existing training-free long-video optimization methods mainly fo…

cs.CV2026

WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching

Weilun Feng, Guoxin Fan, Haotong Qin +10

Diffusion-based world models have shown strong potential for unified world simulation, but the iterative denoising remains too costly for interactive use and long-horizon rollouts.…

cs.CV2026

Semantic-Guided Dynamic Sparsification for Pre-Trained Model-based Class-Incremental Learning

Ruiqi Liu, Boyu Diao, Zijia An +4

Class-Incremental Learning (CIL) requires a model to continually learn new classes without forgetting old ones. A common and efficient solution freezes a pre-trained model and empl…

cs.CV2026

MultiAnimate: Pose-Guided Image Animation Made Extensible

Yingcheng Hu, Haowen Gong, Chuanguang Yang +3

Pose-guided human image animation aims to synthesize realistic videos of a reference character driven by a sequence of poses. While diffusion-based methods have achieved remarkable…

cs.CV2026

Dynamical Adapter Fusion: Constructing A Global Adapter for Pre-Trained Model-based Class-Incremental Learning

Ruiqi Liu, Boyu Diao, Zijia An +3

Class-Incremental Learning (CIL) requires models to continuously acquire new classes without forgetting previously learned ones. A dominant paradigm involves freezing a pre-trained…