Deep, Conspiracy-Driven Storyline: Wake up with no memory of the past.just mysterious powers and a link to a town in Idaho.Unique Disguising Abilities: Consume anyone at anytime, take on their appearances and assume their memories and special abilities.Adaptive parkour lets you move freely through the open-world environments of New York City. Over-the-Top Locomotion & Agility: Seamlessly and fluidly bound from building to building, run up walls, bounce off cars and everything in your path.Change to a shield or armor for defense, or use advanced sensory powers (thermal vision, infected vision) to track your enemies From Claws to Blades to Hammers to Whips, choose the right weapon for the situation. Fast & Deadly Shape-Shifting Combat: Reconfigure your body to the situation at hand.You are the Prototype, Alex Mercer, a man without memory armed with amazing shape-shifting abilities, hunting your way to the heart of the conspiracy which created you making those responsible pay.
Extensive experiments demonstrate that our method: (i) obtain more accurate prototypes (ii) outperforms state-of-the-art techniques by $2% \sim 9%$ in terms of classification accuracy.Includes 53 items: GUN, Call of Duty, Call of Duty: United Offensive, Call of Duty 2, Vampire®: The Masquerade - Bloodlines™, Geometry Wars: Retro Evolved, Call of Duty 4: Modern Warfare, Call of Duty: World at War, Prototype™, 3D Ultra Mini Golf Adventures, Timeshift, Space Quest™ Collection, Aces of The Galaxy, Call of Duty: Modern Warfare 2 (ROW), Singularity, Call of Duty: Black Ops (ROW), Call of Duty: Modern Warfare 3 (ROW), Prototype 2, Call of Duty® - Black Ops II, Call of Duty: Ghosts - Gold Edition, Geometry Wars™ 3: Dimensions Evolved, King's Quest - Chapter 2, King's Quest - Chapter 3, King's Quest - Chapter 4, King's Quest - Chapter 5, Police Quest Collection, Gabriel Knight - Sins of the Fathers, Call of Duty®: Black Ops III - Zombies Chronicles Edition, Gabriel Knight 2: The Beast Within, Gabriel Knight 3: Blood of the Sacred, Blood of the Damned, Arcanum, Phantasmagoria 2, Phantasmagoria, Quest for Glory Collection, Caesar 3, Caesar 4, Call of Duty: Infinite Warfare, Betrayal Collection, Vampire: The Masquerade - Redemption, Police Quest - SWAT, SWAT 3: Tactical Game of the Year Edition, Pharaoh + Cleopatra, Return to Krondor, Zeus + Poseidon, Spycraft: The Great Game, Zork Anthology, Zork: Grand Inquisitor, Zork Nemesis: The Forbidden Lands, Call to Power II, Return to Zork, Police Quest - SWAT 2, Call of Duty: Modern Warfare Remastered, Call of Duty: WWII To avoid the prototype completion error caused by primitive knowledge noises or class differences, we further develop a Gaussian based prototype fusion strategy that combines the mean-based and completed prototypes by exploiting the unlabeled samples. Then, we design a prototype completion network to learn to complete prototypes with these priors. This framework first introduces primitive knowledge (i.e., class-level part or attribute annotations) and extracts representative attribute features as priors. Consequently, we propose a novel prototype completion based meta-learning framework. In this paper, 1) we figure out the key reason, i.e., in the pre-trained feature space, the base classes already form compact clusters while novel classes spread as groups with large variances, which implies that fine-tuning the feature extractor is less meaningful 2) instead of fine-tuning the feature extractor, we focus on estimating more representative prototypes during meta-learning. However, results show that the fine-tuning step makes very marginal improvements. Shipping Information Shipping Availability United States Shipping Policy Standard Ground &.
How precise is the mass of 1kg The Kilogram Prototype mass is +/-1g of 1kg. Pre-training based meta-learning methods effectively tackle the problem by pre-training a feature extractor and then fine-tuning it through the nearest centroid based meta-learning. Prototype Weight: 1 kg (2.2 lb) FAQ How much does this weigh It weighs 1kg.
#Prototype 1 2 code#
This repository contains the code for the paper:īaoquan Zhang, Xutao Li, Yunming Ye, Zhichao Huang, Lisai Zhangįew-shot learning is a challenging task, which aims to learn a classifier for novel classes with few examples. Prototype Completion with Primitive Knowledge for Few-Shot Learning