7 papers
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
SRSR: Enhancing Semantic Accuracy in Real-World Image Super-Resolution with Spatially Re-Focused Text-Conditioning
Chen Chen, Majid Abdolshah, Violetta Shevchenko +3
Existing diffusion-based super-resolution approaches often exhibit semantic ambiguities due to inaccuracies and incompleteness in their text conditioning, coupled with the inherent…
SMARTIES: Spectrum-Aware Multi-Sensor Auto-Encoder for Remote Sensing Images
Gencer Sumbul, Chang Xu, Emanuele Dalsasso +1
From optical sensors to microwave radars, leveraging the complementary strengths of remote sensing (RS) sensors is crucial for achieving dense spatio-temporal monitoring of our pla…
FusionSAM: Visual Multi-Modal Learning with Segment Anything
Daixun Li, Weiying Xie, Mingxiang Cao +5
Multimodal image fusion and semantic segmentation are critical for autonomous driving. Despite advancements, current models often struggle with segmenting densely packed elements d…
Marine Saliency Segmenter: Object-Focused Conditional Diffusion with Region-Level Semantic Knowledge Distillation
Laibin Chang, Yunke Wang, JiaXing Huang +3
Marine Saliency Segmentation (MSS) plays a pivotal role in various vision-based marine exploration tasks. However, existing marine segmentation techniques face the dilemma of objec…
CollagePrompt: A Benchmark for Budget-Friendly Visual Recognition with GPT-4V
Siyu Xu, Yunke Wang, Daochang Liu +2
Recent advancements in generative AI have suggested that by taking visual prompts, GPT-4V can demonstrate significant proficiency in visual recognition tasks. Despite its impressiv…