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arXiv:2408.09042v1 Announce Type: new Abstract: Recovering camera poses from a set of images is a foundational task in 3D computer vision, which powers key applications such as 3D scene/object reconstructions. Classic methods often depend on feature correspondence, such as keypoints, which require the input images to have large overlap and small viewpoint changes. Such requirements present considerable challenges in scenarios with sparse views. Recent data-driven approaches aim to directly output camera poses, either through regressing the 6DoF camera poses or formulating rotation as a probability distribution. However, each approach has its limitations. On one hand, directly regressing the camera poses…

arXiv:2408.09150v1 Announce Type: new Abstract: Piaget's Theory of Cognitive Development (PTC) posits that the development of cognitive levels forms the foundation for human learning across various abilities. As Large Language Models (LLMs) have recently shown remarkable abilities across a wide variety of tasks, we are curious about the cognitive levels of current LLMs: to what extent they have developed and how this development has been achieved. To this end, we construct a benchmark CogLM (Cognitive Ability Evaluation for Language Model) based on PTC to assess the cognitive levels of LLMs. CogLM comprises 1,220 questions spanning 10 cognitive abilities crafted by…

Appen CEO Ryan Kolln recently joined us on the innaugural edition of the Big Data Debrief to talk about Appen’s work in data annotation and labeling, and how the rise of GenAI will impact the world’s appetite for trusted, human-curated data. Appen is one of the leading providers of data annotation and labeling (DAL) solutions. The company, which is traded on the Australian Securities Exchange, has been providing DAL solutions for nearly 30 years. Kolln took the CEO and managing director position this February and recently spoke with Datanami about the company, how the market for DAL solutions is changing,…

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[Submitted on 16 Aug 2024] View a PDF of the paper titled Multi Teacher Privileged Knowledge Distillation for Multimodal Expression Recognition, by Muhammad Haseeb Aslam and 3 other authors View PDF HTML (experimental) Abstract:Human emotion is a complex phenomenon conveyed and perceived through facial expressions, vocal tones, body language, and physiological signals. Multimodal emotion recognition systems can perform well because they can learn complementary and redundant semantic information from diverse sensors. In real-world scenarios, only a subset of the modalities employed for training may be available at test time. Learning privileged information allows a model to exploit data from additional…