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20242026
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cs.CV2026

GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed

Qize Yu, Lianrui Fan, Bowen Ping +19

Autoregressive (AR) grounding models serialize spatial predictions, introducing sequential latency and imposing a causal order on output tokens. We view grounding as visual evidenc…

cs.CV2026

CameraEditor: Camera-Controlled Image Editing via Video-Prior Sequential Modeling

Xin Shen, Chengyou Jia, Keshuo Xing +6

Beyond semantic content, camera parameters play a pivotal role in dictating the geometric perspective and appearance of any given image. While recent image editing models excel at…

cs.CV2026

OmniTryOn: Video Try-On Anything at Once!

Changliang Xia, Chengyou Jia, Minnan Luo +3

Although video virtual try-on (VVT) has achieved significant progress, existing methods still exhibit two fundamental limitations: first, they are restricted to single-garment tran…

cs.CV2026

-Predictor: Noise-Free Deterministic Diffusion for Dense Prediction

Changliang Xia, Chengyou Jia, Minnan Luo +3

Although diffusion models with strong visual priors have emerged as powerful dense prediction backbones, they overlook a core limitation: the stochastic noise at the core of diffus…

cs.CV2025

PaCo-RL: Advancing Reinforcement Learning for Consistent Image Generation with Pairwise Reward Modeling

Bowen Ping, Chengyou Jia, Minnan Luo +4

Consistent image generation requires faithfully preserving identities, styles, and logical coherence across multiple images, which is essential for applications such as storytellin…