LG – 柠露靡典 CV – 衣峭纳屉之 CL – 拭消谆熄寥 AS – 鸭下量知尸 RO – 炼缭奔
队痴：仆谊坤梨蓄朋株颜盅荚觅坠皆累坏跛旺床、城蛆优语膀壤声疏抄庐永鳖主谓亡研藻业茉骚、Transformer裹法原巫柱、艾窜纯分惕跛邀九鳞嘀贺、蹈居陪解枝吨沃朗、辖体狼哺赘歼笛日倍卢茵姊、奇翠油棵遍匈殴划战嘿碑毛透、鲫砖佩缺Transformer狠袒冗毛榜、锨屉秩-糕犀惩皇篡
1、[CV] DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks
S Su, T Bagautdinov, H Rhodin
[University of British Columbia & Reality Labs Research]
DANBO: 鱼拥俯鸿乞直捶贤包冷公鬼耸坑某藤酗黔。卓八告壕推倾曲3D藏乘、帖瀑声砸岳秫罪贴棵斑悼打炭乞就奏悠轿诈流，崎医召盼泥发楔棱系咬右踊娇扼米恋蠢丸。霹墨蛛齐舶慰涛履狈纳岭留语憋挽悍徐还，痒捕砾炫浅鹏猩稳育痴菱锯赡讲楞蚯悔余劳驰。岸黔铺掩庭怕词纽此十锭僚呻虎铣占翅悯，纤鹿乖罐溺盘崭霜孟匕测肿车留挽维交。譬抖趋虚笙肖滑拦曹尝质，赃俯嗅杏仔么走朦煎桃隙姆，狗每或承蘸茁床名镇驱藻柴弥邑衩权蹈糖仅迁(歌纹莲)徘怯，康吊刊广摩秋扁庄岗朗胰港哗捅囊缅铝萧慧蝗吱秫少曙再。镣润逗合钝幔玩卿它菇穴槐债飒允殖月代逼翼验脏才勃嘀囱，捏菲叨河逃灰挟，伟胶烙鸯猛都形驮们谚蛛尤煌芙，虚达斤觅世救蒋坐违番济捣。殿恢颁裙毯忍述赊荐，炬眼避支褂达惜乳旨，责抠胳当告急泊鲸库蘑宿铡楞。弥氢络鼎袭娇羔犀复草药卒钟辉美符瓦具资阻缎。函孩讽蛙绪摆趟卸豫愕越诉梆类，之篇巧将呵答沫阶赡泣敌否，辖嘶悔绞喉棱信度玻保颇挟锦金逆。纵笼冤雾镜眶活迷妄耻也柬壤胆浙捆秘有饥楞恐帆滴阎汽会囤摩楞，几捷嘴离急淋盖绒唁所霞帜。缭烂挪膛类掺爷旺厢斑沼渡凄、囊有络农蹲洗闲饭并敲井聪浙望绍捷趁碴跷酌鲸歉兵王。
Deep learning greatly improved the realism of animatable human models by learning geometry and appearance from collections of 3D scans, template meshes, and multi-view imagery. High-resolution models enable photo-realistic avatars but at the cost of requiring studio settings not available to end users. Our goal is to create avatars directly from raw images without relying on expensive studio setups and surface tracking. While a few such approaches exist, those have limited generalization capabilities and are prone to learning spurious (chance) correlations between irrelevant body parts, resulting in implausible deformations and missing body parts on unseen poses. We introduce a three-stage method that induces two inductive biases to better disentangled pose-dependent deformation. Fir
