Edit-Compass and EditReward-Compass are new unified benchmarks for fine-grained image editing evaluation and realistic reward modeling in reinforcement learning optimization.
Alvarez, Jun Gao, Sanja Fidler, Zian Wang, and Huan Ling
6 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 6representative citing papers
Progressive semantic image simplification uses VLMs and a verifier to iteratively remove and inpaint scene elements while preserving photorealism, distilled into an image-to-video model for direct sequence prediction.
PhysEdit introduces adaptive reasoning depth and spatial masking to make image editing faster and more instruction-aligned without retraining the base model.
PhyEdit improves physical accuracy in image object manipulation by using explicit geometric simulation as 3D-aware guidance combined with joint 2D-3D supervision.
JoyAI-Image unifies visual understanding and generation via an MLLM-MMDiT architecture with spatial training signals to reach competitive benchmark performance and stronger spatial intelligence.
citing papers explorer
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Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling
Edit-Compass and EditReward-Compass are new unified benchmarks for fine-grained image editing evaluation and realistic reward modeling in reinforcement learning optimization.
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Progressive Photorealistic Simplification
Progressive semantic image simplification uses VLMs and a verifier to iteratively remove and inpaint scene elements while preserving photorealism, distilled into an image-to-video model for direct sequence prediction.
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PhysEdit: Physically-Consistent Region-Aware Image Editing via Adaptive Spatio-Temporal Reasoning
PhysEdit introduces adaptive reasoning depth and spatial masking to make image editing faster and more instruction-aligned without retraining the base model.
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PhyEdit: Towards Real-World Object Manipulation via Physically-Grounded Image Editing
PhyEdit improves physical accuracy in image object manipulation by using explicit geometric simulation as 3D-aware guidance combined with joint 2D-3D supervision.
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JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation
JoyAI-Image unifies visual understanding and generation via an MLLM-MMDiT architecture with spatial training signals to reach competitive benchmark performance and stronger spatial intelligence.
- UniGeo: Unifying Geometric Guidance for Camera-Controllable Image Editing via Video Models