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Detecting Trojaned DNNs Using Counterfactual Attributions
We target the problem of detecting Trojans or backdoors in DNNs. Such mo...
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Zero-Shot Learning with Knowledge Enhanced Visual Semantic Embeddings
We improve zero-shot learning (ZSL) by incorporating common-sense knowle...
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RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization
We study an important, yet largely unexplored problem of large-scale cro...
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Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks
We introduce Deep Adaptive Semantic Logic (DASL), a novel framework for ...
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Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation
While models for Visual Question Answering (VQA) have steadily improved ...
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FoodX-251: A Dataset for Fine-grained Food Classification
Food classification is a challenging problem due to the large number of ...
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Deep Unified Multimodal Embeddings for Understanding both Content and Users in Social Media Networks
There has been an explosion of multimodal content generated on social me...
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Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts
Computing author intent from multimodal data like Instagram posts requir...
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Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment
We address the problem of grounding free-form textual phrases by using w...
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Semantically-Aware Attentive Neural Embeddings for Image-based Visual Localization
We present a novel method for fusing appearance and semantic information...
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Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention
We tackle the problem of understanding visual ads where given an ad imag...
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Zero-Shot Object Detection
We introduce and tackle the problem of zero-shot object detection (ZSD),...
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Combining Weakly and Webly Supervised Learning for Classifying Food Images
Food classification from images is a fine-grained classification problem...
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AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos
We propose a novel method for temporally pooling frames in a video for t...
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Discriminatively Trained Latent Ordinal Model for Video Classification
We study the problem of video classification for facial analysis and hum...
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LOMo: Latent Ordinal Model for Facial Analysis in Videos
We study the problem of facial analysis in videos. We propose a novel we...
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Deep Active Object Recognition by Joint Label and Action Prediction
An active object recognition system has the advantage of being able to a...
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Pseudo vs. True Defect Classification in Printed Circuits Boards using Wavelet Features
In recent years, Printed Circuit Boards (PCB) have become the backbone o...
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