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Minh-Triet Tran

6 papers indexed

arxivcs.CV2026-07-09

SAGA: Stable Acceleration Guidance for Autoregressive Video Generation

Thanh-Nhan Vo, Trong-Thuan Nguyen, Trung-Hoang Le, Tam V. Nguyen, Minh-Triet Tran

Autoregressive video diffusion enables efficient streaming and long-horizon video generation, but repeatedly reusing generated latents as causal context can amplify temporal errors, resulting in flickering, motion jitter, and structural drift. In this paper, we investigate this f…

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arxivcs.CV2026-07-08

SoccerNet 2026 Challenges Results

Anthony Cioppa, Silvio Giancola, Håkan Ardö, Mohamad Dalal, Jan Held, Jérémie Ochin, et al.

The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in sports video understanding. This year's challenges span five vision-based tasks: (1) Ball Action Anticipation, predictin…

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arxivcs.CV2026-07-03

PhysMirror: Physics-Aware Mirror Object Generation

Xuan-Bach Mai, Duy-Phuc Nguyen, Quoc-Van Le, Tam V. Nguyen, Thanh-Toan Do, Huu Le, et al.

Synthesizing physically accurate mirror reflections remains a fundamental challenge for modern text-to-image diffusion models, which are increasingly critical for generating synthetic training data for embodied AI and robotic perception. These models typically struggle with stric…

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arxivcs.CV2026-06-29

SADL: What to Ignore? A Benchmark for Subject-Aware Distractor Localization

Cao-Tri Nguyen, Nguyen-Khoa Luong, Vinh-Tiep Nguyen, Minh-Triet Tran

Photographs frequently contain \emph{visual distractors} besides foregrounds and backgrounds of the intended subject, competing for attention and weakening composition. While modern editing tools streamline object removal, identifying which objects to remove remains a mostly manu…

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arxivcs.CV2026-06-26

AI-Generated Image Recognition via Fusion of CNNs and Vision Transformers

Xuan-Bach Mai, Hoang-Minh Nguyen-Huu, Quoc-Nghia Nguyen, Hoang-Tung Vu, Minh-Triet Tran, Trung-Nghia Le

Recent advancements in synthetic data technology have opened a new era where images of remarkable quality are generated, blurring the lines between real-life images and those produced by Artificial Intelligence (AI). This evolution poses a significant challenge to ensuring the re…

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