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| 5 Conclusion from an Automation Expert with Firsthand Knowledge of Highway Regulation What Self-Driving Cars | tell | Us About AI Risks: Missy Cummings |
| Aligning Where to See and What to | tell | : Image Captioning with Region-Based Attention and Scene-Specific Contexts |
| Batch Normalization | tell | s You Which Filter is Important |
| Can a camera | tell | the weather? |
| Can Your Eyes | tell | Me How You Think? A Gaze Directed Estimation of the Mental Activity |
| Completely Automated Public Turing Test to | tell | Computers and Humans Apart, CAPTCHA, Generation, Breaking |
| Deep Relative Distance Learning: | tell | the Difference between Similar Vehicles |
| Delay Metric for Video Object Detection: What Average Precision Fails to | tell | , A |
| Deriving Stand Structural Complexity from Airborne Laser Scanning Data: What Does It | tell | Us about a Forest? |
| Discovering Potential Settlement Areas around Archaeological | tell | s Using the Integration between Historic Topographic Maps, Optical, and Radar Data in the Northern Nile Delta, Egypt |
| Does A Body Image | tell | Age? |
| Every Picture | tell | s a Story: Generating Sentences from Images |
| Explore and | tell | : Embodied Visual Captioning in 3D Environments |
| Eyes have it: New iris-recognition techniques can | tell | whether an Eye is healthy, diseased: or dead, The |
| Face | tell | s Detailed Expression: Generating Comprehensive Facial Expression Sentence Through Facial Action Units |
| From Show to | tell | : A Survey on Deep Learning-Based Image Captioning |
| GLocal | tell | s you more: Coupling GLocal structural for feature selection with sparsity for image and video classification |
| How a Digital Computer Can | tell | Whether a Line is Straight |
| How Can You | tell | if Two Line Drawings Are the Same? |
| How Do You | tell | a Blackbird from a Crow? |
| How To | tell | Right From Left |
| How to | tell | the difference between a cat and a dog? |
| Image retrieval on compressed images: Can we | tell | the difference? |
| Informative Object Annotations: | tell | Me Something I Don't Know |
| Let me | tell | you about your personality! -- Real-time personality prediction from nonverbal behavioural cues |
| Let the robot | tell | : Describe car image with natural language via LSTM |
| Mirror, mirror on the wall, | tell | me, is the error small? |
| Move Forward and | tell | : A Progressive Generator of Video Descriptions |
| Neurocalibration: A Neural Network That Can | tell | Camera Calibration Parameters |
| On Random Field Completely Automated Public Turing Test to | tell | Computers and Humans Apart Generation |
| Only Time Can | tell | : Discovering Temporal Data for Temporal Modeling |
| Out-of-Distribution Identification: Let Detector | tell | Which I Am Not Sure |
| Protect, show, attend and | tell | : Empowering image captioning models with ownership protection |
| Rain-Use-Efficiency: What it | tell | s us about the Conflicting Sahel Greening and Sahelian Paradox |
| Sa | tell | ite Imagery Analysis: What Can Hospital Parking Lots Tell Us about a Disease Outbreak? |
| Show and | tell | in the Loop: Cross-Modal Circular Correlation Learning |
| Show and | tell | : A neural image caption generator |
| Show and | tell | : Lessons Learned from the 2015 MSCOCO Image Captioning Challenge |
| Show Me What and | tell | Me How: Video Synthesis via Multimodal Conditioning |
| Show me your face and I will | tell | you your height, weight and body mass index |
| Show, Adapt and | tell | : Adversarial Training of Cross-Domain Image Captioner |
| Show, Conceive and | tell | : Image Captioning with Prospective Linguistic Information |
| Show, Control and | tell | : A Framework for Generating Controllable and Grounded Captions |
| Show, Deconfound and | tell | : Image Captioning with Causal Inference |
| Show, Edit and | tell | : A Framework for Editing Image Captions |
| Show, | tell | and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data |
| Show, | tell | and Rephrase: Diverse Video Captioning via Two-Stage Progressive Training |
| Show, | tell | and Summarize: Dense Video Captioning Using Visual Cue Aided Sentence Summarization |
| Show, | tell | , and Polish: Ruminant Decoding for Image Captioning |
| Show, Translate and | tell | |
| Sign, Attend and | tell | : Spatial Attention for Sign Language Recognition |
| Space-Time Behavior-Based Correlation - OR - How to | tell | If Two Underlying Motion Fields Are Similar Without Computing Them? |
| State of the Art: This Convolutional Neural Network can | tell | you Whether a Painting is a Fake |
| tell | as You Imagine: Sentence Imageability-aware Image Captioning |
| tell | Me about TV Commercials of This Product |
| tell | Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generation |
| tell | Me What You Like and I'll Tell You What You Are: Discriminating Visual Preferences on Flickr Data |
| tell | Me What You Like and I'll Tell You What You Are: Discriminating Visual Preferences on Flickr Data |
| tell | Me What You See and I Will Show You Where It Is |
| tell | Me Where I Am: Object-Level Scene Context Prediction |
| tell | Me Where to Look: Guided Attention Inference Network |
| tell | the Story of Ancient Thracians Through Serious Game |
| tell | Your Story: Text-Driven Face Video Synthesis with High Diversity via Adversarial Learning |
| tell | , Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction |
| Transform and | tell | : Entity-Aware News Image Captioning |
| Transform, contrast and | tell | : Coherent entity-aware multi-image captioning |
| Two Coupled Rejection Metrics Can | tell | Adversarial Examples Apart |
| Using character recognition and segmentation to | tell | computer from humans |
| Watch, Listen and | tell | : Multi-Modal Weakly Supervised Dense Event Captioning |
| What a Histogram Can Really | tell | the Classifier |
| What Can an Image of a Smooth Lambertian Surface | tell | About Camera Nonlinearity? |
| What Can Casual Walkers | tell | Us About A 3D Scene? |
| What Can Expressive Semantics | tell | : Retrieval Model for a Flash-Movie Search Engine |
| What Can I | tell | from Your Face? |
| What can missing correspondences | tell | us about 3D structure and motion? |
| What Can Multifractal Analysis | tell | Us about Hyperspectral Imagery? |
| What Can Pictures | tell | Us About Web Pages? Improving Document Search Using Images |
| What Can Projections of Flow Fields | tell | Us About Visual Motion |
| What Can Two Images | tell | Us about a Third One? |
| What do 15,000 object categories | tell | us about classifying and localizing actions? |
| What Do Different Evaluation Metrics | tell | Us About Saliency Models? |
| What do features | tell | about images? |
| What Do Four Points in Two Calibrated Images | tell | Us about the Epipoles? |
| What do N photographs | tell | us about 3D shape? |
| What Do Planar Shadows | tell | Us About Scene Geometry? |
| What Do the Sun and Sky | tell | Us About the Camera? |
| What Do the Sun and the Sky | tell | Us About the Camera? |
| What Does 2D Geometric Information Really | tell | Us About 3D Face Shape? |
| What Does Classifying More Than 10,000 Image Categories | tell | Us? |
| What Does Digital Straightness | tell | about Digital Convexity? |
| What does scene text | tell | us? |
| What Does the Occluding Contour | tell | Us About Solid Shape? |
| What Does the Sky | tell | Us about the Camera? |
| What entropy | tell | s about man-made structures |
| What Face and Body Shapes Can | tell | Us About Height |
| What Four Decades of Earth Observation | tell | Us about Land Degradation in the Sahel? |
| What Genes | tell | about Iris Appearance |
| What Rainfall Does Not | tell | Us: Enhancing Financial Instruments with Satellite-Derived Soil Moisture and Evaporative Stress |
| You Can (Sometimes) | tell | an Image by Its Cover |
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