Papers Image Cropping
“Image Cropping” 태그가 달린 논문 100편 · 필터 해제
EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI
Convolutional neural networks (CNNs) have demonstrated encouraging results in image classification tasks. However, the prohibitive computational cost of CNNs hinders the deployment of CNNs onto resource-constrained embed…
Image ClassificationModel CompressionImage CroppingSmart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising for edge AI. However, as an image usually contains much spatial redund…
Image CroppingVistaHop: Benchmarking Long-Horizon Visual DeepSearch
Visual DeepSearch tasks require multimodal large language models (MLLMs) to resolve complex visual queries by repeatedly inspecting image regions, grounding reasoning in visual evidence, and connecting fine-grained clues…
Question AnsweringVisual GroundingVisual ReasoningImage CroppingCROP: Expert-Aligned Image Cropping via Compositional Reasoning and Optimizing Preference
Aesthetic image cropping aims to enhance the aesthetic quality of an image by improving its composition through spatial cropping. Previous methods often rely on saliency prediction or retrieval augmentation, ignoring the…
Multimodal ReasoningSaliency PredictionImage CroppingCharTool: Tool-Integrated Visual Reasoning for Chart Understanding
Charts are ubiquitous in scientific and financial literature for presenting structured data. However, chart reasoning remains challenging for multimodal large language models (MLLMs) due to the lack of high-quality train…
Reinforcement LearningVisual GroundingVisual ReasoningImage CroppingLearning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs
To enhance the perception and reasoning capabilities of multimodal large language models in complex visual scenes, recent research has introduced agent-based workflows. In these works, MLLMs autonomously utilize image cr…
Reinforcement LearningQuestion AnsweringImage CroppingScale-Aware UAV-to-Satellite Cross-View Geo-Localization: A Semantic Geometric Approach
Cross-View Geo-Localization (CVGL) between UAV imagery and satellite images plays a crucial role in target localization and UAV self-positioning. However, most existing methods rely on the idealized assumption of scale c…
Image CroppingDISC: Dense Integrated Semantic Context for Large-Scale Open-Set Semantic Mapping
Open-set semantic mapping enables language-driven robotic perception, but current instance-centric approaches are bottlenecked by context-depriving and computationally expensive crop-based feature extraction. To overcome…
Image CroppingWhat if Agents Could Imagine? Reinforcing Open-Vocabulary HOI Comprehension through Generation
Multimodal Large Language Models have shown promising capabilities in bridging visual and textual reasoning, yet their reasoning capabilities in Open-Vocabulary Human-Object Interaction (OV-HOI) are limited by cross-moda…
Reinforcement LearningImage CroppingSenseNova-MARS: Empowering Multimodal Agentic Reasoning and Search via Reinforcement Learning
While Vision-Language Models (VLMs) can solve complex tasks through agentic reasoning, their capabilities remain largely constrained to text-oriented chain-of-thought or isolated tool invocation. They fail to exhibit the…
Reinforcement LearningVisual ReasoningImage CroppingEnhancing Small Object Detection with YOLO: A Novel Framework for Improved Accuracy and Efficiency
This paper investigates and develops methods for detecting small objects in large-scale aerial images. Current approaches for detecting small objects in aerial images often involve image cropping and modifications to det…
Small Object DetectionImage CroppingSeeing Straight: Document Orientation Detection for Efficient OCR
Despite significant advances in document understanding, determining the correct orientation of scanned or photographed documents remains a critical pre-processing step in the real world settings. Accurate rotation correc…
Image CroppingCarousel: A High-Resolution Dataset for Multi-Target Automatic Image Cropping
Automatic image cropping is a method for maximizing the human-perceived quality of cropped regions in photographs. Although several works have proposed techniques for producing singular crops, little work has addressed t…
Image CroppingAesCrop: Aesthetic-driven Cropping Guided by Composition
Aesthetic-driven image cropping is crucial for applications like view recommendation and thumbnail generation, where visual appeal significantly impacts user engagement. A key factor in visual appeal is composition--the …
Image CroppingGroundSight: Augmenting Vision-Language Models with Grounding Information and De-hallucination
We propose a method to improve Visual Question Answering (VQA) with Retrieval-Augmented Generation (RAG) by introducing text-grounded object localization. Rather than retrieving information based on the entire image, our…
Visual Question AnsweringObject LocalizationImage CroppingSimple o3: Towards Interleaved Vision-Language Reasoning
Multimodal Large Language Models (MLLMs) have shown impressive performance on vision-language tasks, but their long Chain-of-Thought (CoT) capabilities in multimodal scenarios remain underexplored. Inspired by OpenAI's o…
Multimodal ReasoningVisual GroundingVisual ReasoningImage CroppingMulti-Label Plant Species Prediction with Metadata-Enhanced Multi-Head Vision Transformers
We present a multi-head vision transformer approach for multi-label plant species prediction in vegetation plot images, addressing the PlantCLEF 2025 challenge. The task involves training models on single-species plant i…
Image CroppingEnhancing DR Classification with Swin Transformer and Shifted Window Attention
Diabetic retinopathy (DR) is a leading cause of blindness worldwide, underscoring the importance of early detection for effective treatment. However, automated DR classification remains challenging due to variations in i…
Data AugmentationImage CroppingBoosting Resolution Generalization of Diffusion Transformers with Randomized Positional Encodings
Resolution generalization in image generation tasks enables the production of higher-resolution images with lower training resolution overhead. However, a significant challenge in resolution generalization, particularly …
Data AugmentationImage CroppingImage GenerationPositionACE: Anatomically Consistent Embeddings in Composition and Decomposition
Medical images acquired from standardized protocols show consistent macroscopic or microscopic anatomical structures, and these structures consist of composable/decomposable organs and tissues, but existing self-supervis…
Few-Shot LearningImage CroppingSelf-Supervised Learning